Cure Model Regression
cureit.RdCure Model Regression
Usage
# S3 method for formula
cureit(
surv_formula,
cure_formula,
data,
conf.level = 0.95,
nboot = 100,
eps = 1e-07,
...
)
cureit(object, ...)
# S3 method for default
cureit(object, ...)Arguments
- surv_formula
formula with
Surv()on LHS and covariates on RHS.- cure_formula
formula with covariates for cure fraction on RHS
- data
data frame
- conf.level
confidence level. Default is 0.95.
- nboot
number of bootstrap samples used for inference.
- eps
convergence criterion for the EM algorithm.
- ...
passed to methods
- object
input object
See also
Other cureit() functions:
Brier_inference_bootstrap(),
broom_methods_cureit,
nomogram(),
predict.cureit()
Examples
cureit(surv_formula = Surv(ttdeath, death) ~ age + grade,
cure_formula = ~ age + grade, data = trial)
#> 0 were not able to fit
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002616112 0.569504769 0.345883977
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.575003030 0.009813492 0.108542405
#> grade_iii, Cure model
#> 0.823899189
#>
#> $surv_formula
#> Surv(ttdeath, death) ~ age + grade
#> <environment: 0x564adda8e038>
#>
#> $cure_formula
#> ~age + grade
#> <environment: 0x564adda8e038>
#>
#> $data
#> # A tibble: 200 × 8
#> trt age marker stage grade response death ttdeath
#> <chr> <dbl> <dbl> <fct> <fct> <int> <dbl> <dbl>
#> 1 Drug A 23 0.16 T1 II 0 0 24
#> 2 Drug B 9 1.11 T2 I 1 0 24
#> 3 Drug A 31 0.277 T1 II 0 0 24
#> 4 Drug A NA 2.07 T3 III 1 1 17.6
#> 5 Drug A 51 2.77 T4 III 1 1 16.4
#> 6 Drug B 39 0.613 T4 I 0 1 15.6
#> 7 Drug A 37 0.354 T1 II 0 0 24
#> 8 Drug A 32 1.74 T1 I 0 1 18.4
#> 9 Drug A 31 0.144 T1 II 0 0 24
#> 10 Drug B 34 0.205 T3 I 0 1 10.5
#> # ℹ 190 more rows
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> $surv_xlevels$grade
#> [1] "I" "II" "III"
#>
#>
#> $cure_xlevels
#> $cure_xlevels$grade
#> [1] "I" "II" "III"
#>
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 7
#> term estimate std.error statistic conf.low conf.high p.value
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure mod… -0.575 0.526 -1.09 -1.61 0.456 0.275
#> 2 age, Cure model 0.00981 0.0101 0.970 -0.0100 0.0296 0.332
#> 3 grade_ii, Cure model 0.109 0.351 0.309 -0.579 0.796 0.757
#> 4 grade_iii, Cure model 0.824 0.375 2.20 0.0893 1.56 0.0279
#>
#> $tidy$df_surv
#> # A tibble: 3 × 7
#> term estimate std.error statistic conf.low conf.high p.value
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00262 0.00814 -0.321 -0.0186 0.0133 0.748
#> 2 grade_ii, Survival mo… 0.570 0.297 1.92 -0.0126 1.15 0.0552
#> 3 grade_iii, Survival m… 0.346 0.222 1.56 -0.0892 0.781 0.119
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.575003 0.009813 0.108542 0.823899
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 253.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.575003030 0.009813492 0.108542405 0.823899189
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002616112 0.569504769 0.345883977
#>
#> $b_var
#> [1] 0.2769083741 0.0001023678 0.1231648254 0.1404811974
#>
#> $b_sd
#> [1] 0.5262208 0.0101177 0.3509485 0.3748082
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.0927029 0.9699336 0.3092830 2.1981887
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.27452427 0.33207961 0.75710624 0.02793566
#>
#> $beta_var
#> [1] 6.631273e-05 8.820734e-02 4.927252e-02
#>
#> $beta_sd
#> [1] 0.008143263 0.296997213 0.221974144
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.3212609 1.9175425 1.5582174
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.74801270 0.05516905 0.11918172
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.000000000 0.000000000 0.000000000 0.604678067 0.658063410 0.000000000
#> [7] 0.417229340 0.000000000 0.879376354 0.000000000 0.000000000 0.744886187
#> [13] 0.787600867 0.142672058 0.944518547 0.000000000 0.693100768 0.000000000
#> [19] 0.000000000 0.000000000 0.000000000 0.540871173 0.006912639 0.976381134
#> [25] 0.640373656 0.000000000 0.000000000 0.684419417 0.522291631 0.000000000
#> [31] 0.278243702 0.000000000 0.000000000 0.000000000 0.246976530 0.821307758
#> [37] 0.000000000 0.666890646 0.466018936 0.456394953 0.829660071 0.854634203
#> [43] 0.000000000 0.531599829 0.000000000 0.000000000 0.000000000 0.846335953
#> [49] 0.446649365 0.887603756 0.000000000 0.000000000 0.368370905 0.837991986
#> [55] 0.736284601 0.368370905 0.762052697 0.904005497 0.000000000 0.130947018
#> [61] 0.000000000 0.000000000 0.178167087 0.000000000 0.298558895 0.093531067
#> [67] 0.960518552 0.000000000 0.000000000 0.000000000 0.000000000 0.387858887
#> [73] 0.968455884 0.020860827 0.613665875 0.000000000 0.753465281 0.000000000
#> [79] 0.000000000 0.000000000 0.586773524 0.036370054 0.000000000 0.427038837
#> [85] 0.267747949 0.984266892 0.106209363 0.895813391 0.000000000 0.000000000
#> [91] 0.727657186 0.397671772 0.000000000 0.246976530 0.631469660 0.920311545
#> [97] 0.000000000 0.000000000 0.000000000 0.348502061 0.550166021 0.862915985
#> [103] 0.436874482 0.000000000 0.494318881 0.513013956 0.000000000 0.118522726
#> [109] 0.000000000 0.503694197 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.779118376 0.649247645 0.000000000 0.992139734 0.308649170
#> [121] 0.080274841 0.568542449 0.000000000 0.000000000 0.718999352 0.475516896
#> [127] 0.000000000 0.201867710 0.000000000 0.000000000 0.224987874 0.796088245
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.912176411 0.000000000
#> [139] 0.000000000 0.000000000 0.952539418 0.318644852 0.000000000 0.000000000
#> [145] 0.236117909 0.804529313 0.770582430 0.000000000 0.701722215 0.328677697
#> [151] 0.871155498 0.000000000 0.000000000 0.000000000 0.000000000 0.065734870
#> [157] 0.000000000 0.338572747 0.675684959 0.050684149 0.154512416 0.358472658
#> [163] 0.559374570 0.000000000 0.000000000 0.000000000 0.189977968 0.000000000
#> [169] 0.812910823 0.000000000 0.407438340 0.710355937 0.577676416 0.000000000
#> [175] 0.936485829 0.484909262 0.000000000 0.000000000 0.928419678 0.622583868
#> [181] 0.288505592 0.000000000 0.586773524 0.000000000 0.166456957 0.000000000
#> [187] 0.213576414 0.000000000 0.000000000
#>
#> $Time
#> 1 2 3 5 6 7 8 9 10 11 12 13 14
#> 24.00 24.00 24.00 16.43 15.64 24.00 18.43 24.00 10.53 24.00 24.00 14.34 12.89
#> 15 16 17 18 19 20 21 22 23 24 25 26 27
#> 22.68 8.71 24.00 15.21 24.00 24.00 24.00 24.00 16.92 23.89 6.32 15.77 24.00
#> 28 29 30 31 32 33 34 35 36 37 38 39 40
#> 24.00 15.45 17.43 24.00 20.90 24.00 24.00 24.00 21.19 12.52 24.00 15.59 18.00
#> 41 42 43 44 45 46 47 48 49 51 52 53 54
#> 18.02 12.43 12.10 24.00 17.42 24.00 24.00 24.00 12.19 18.23 10.42 24.00 24.00
#> 55 56 57 58 60 61 62 63 64 65 66 67 68
#> 19.34 12.21 14.46 19.34 13.15 10.12 24.00 22.77 24.00 24.00 22.13 24.00 20.62
#> 69 70 71 72 74 75 76 77 78 79 80 81 82
#> 23.23 7.38 24.00 24.00 24.00 24.00 19.22 7.27 23.88 16.23 24.00 14.06 24.00
#> 83 84 85 86 87 88 90 91 92 93 94 95 96
#> 24.00 24.00 16.44 23.81 24.00 18.37 20.94 5.33 22.92 10.33 24.00 24.00 14.54
#> 97 98 99 100 101 102 103 104 105 106 107 108 109
#> 19.14 24.00 21.19 16.07 9.97 24.00 24.00 24.00 19.75 16.67 11.18 18.29 24.00
#> 110 111 112 113 116 117 118 119 120 121 122 123 125
#> 17.56 17.45 24.00 22.86 24.00 17.46 24.00 24.00 24.00 24.00 24.00 13.00 15.65
#> 126 127 128 129 130 131 132 133 134 135 136 137 138
#> 24.00 3.53 20.35 23.41 16.47 24.00 24.00 14.65 17.81 24.00 21.83 24.00 24.00
#> 139 140 141 142 143 144 145 146 147 148 149 150 151
#> 21.49 12.68 24.00 24.00 24.00 24.00 10.07 24.00 24.00 24.00 8.37 20.33 24.00
#> 152 153 154 155 156 157 158 159 160 161 162 163 164
#> 24.00 21.33 12.63 13.08 24.00 15.10 20.14 10.55 24.00 24.00 24.00 24.00 23.60
#> 165 166 167 168 169 170 171 172 173 174 175 176 177
#> 24.00 19.98 15.55 23.72 22.41 19.54 16.57 24.00 24.00 24.00 21.91 24.00 12.53
#> 178 179 180 181 182 183 184 185 186 187 188 190 191
#> 24.00 18.63 14.82 16.46 24.00 9.24 17.77 24.00 24.00 9.92 16.16 20.81 24.00
#> 192 193 194 196 197 198 200
#> 16.44 24.00 22.40 24.00 21.60 24.00 24.00
#>
#> $bootstrap_fit
#> $bootstrap_fit[[1]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.005677755 0.653133672 0.135991334
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.014200031 0.002146869 -0.387889956
#> grade_iii, Cure model
#> 0.801130099
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 45 17.42 1 54 0 1
#> 158 20.14 1 74 1 0
#> 10 10.53 1 34 0 0
#> 40 18.00 1 28 1 0
#> 177 12.53 1 75 0 0
#> 5 16.43 1 51 0 1
#> 189 10.51 1 NA 1 0
#> 183 9.24 1 67 1 0
#> 24 23.89 1 38 0 0
#> 154 12.63 1 20 1 0
#> 124 9.73 1 NA 1 0
#> 76 19.22 1 54 0 1
#> 49 12.19 1 48 1 0
#> 96 14.54 1 33 0 1
#> 140 12.68 1 59 1 0
#> 99 21.19 1 38 0 1
#> 123 13.00 1 44 1 0
#> 194 22.40 1 38 0 1
#> 66 22.13 1 53 0 0
#> 15 22.68 1 48 0 0
#> 170 19.54 1 43 0 1
#> 81 14.06 1 34 0 0
#> 124.1 9.73 1 NA 1 0
#> 170.1 19.54 1 43 0 1
#> 36 21.19 1 48 0 1
#> 168 23.72 1 70 0 0
#> 5.1 16.43 1 51 0 1
#> 180 14.82 1 37 0 0
#> 69 23.23 1 25 0 1
#> 50 10.02 1 NA 1 0
#> 153 21.33 1 55 1 0
#> 150 20.33 1 48 0 0
#> 113 22.86 1 34 0 0
#> 85 16.44 1 36 0 0
#> 105 19.75 1 60 0 0
#> 129 23.41 1 53 1 0
#> 192 16.44 1 31 1 0
#> 13 14.34 1 54 0 1
#> 66.1 22.13 1 53 0 0
#> 78 23.88 1 43 0 0
#> 192.1 16.44 1 31 1 0
#> 90 20.94 1 50 0 1
#> 187 9.92 1 39 1 0
#> 194.1 22.40 1 38 0 1
#> 155 13.08 1 26 0 0
#> 10.1 10.53 1 34 0 0
#> 58 19.34 1 39 0 0
#> 30 17.43 1 78 0 0
#> 183.1 9.24 1 67 1 0
#> 107 11.18 1 54 1 0
#> 101 9.97 1 10 0 1
#> 149 8.37 1 33 1 0
#> 128 20.35 1 35 0 1
#> 145 10.07 1 65 1 0
#> 78.1 23.88 1 43 0 0
#> 45.1 17.42 1 54 0 1
#> 23 16.92 1 61 0 0
#> 133 14.65 1 57 0 0
#> 77 7.27 1 67 0 1
#> 63 22.77 1 31 1 0
#> 166 19.98 1 48 0 0
#> 77.1 7.27 1 67 0 1
#> 39 15.59 1 37 0 1
#> 170.2 19.54 1 43 0 1
#> 110 17.56 1 65 0 1
#> 167 15.55 1 56 1 0
#> 187.1 9.92 1 39 1 0
#> 6 15.64 1 39 0 0
#> 157 15.10 1 47 0 0
#> 57 14.46 1 45 0 1
#> 164 23.60 1 76 0 1
#> 8 18.43 1 32 0 0
#> 60 13.15 1 38 1 0
#> 5.2 16.43 1 51 0 1
#> 26 15.77 1 49 0 1
#> 155.1 13.08 1 26 0 0
#> 96.1 14.54 1 33 0 1
#> 36.1 21.19 1 48 0 1
#> 69.1 23.23 1 25 0 1
#> 159 10.55 1 50 0 1
#> 8.1 18.43 1 32 0 0
#> 49.1 12.19 1 48 1 0
#> 86 23.81 1 58 0 1
#> 167.1 15.55 1 56 1 0
#> 37 12.52 1 57 1 0
#> 69.2 23.23 1 25 0 1
#> 111 17.45 1 47 0 1
#> 114 13.68 1 NA 0 0
#> 150.1 20.33 1 48 0 0
#> 8.2 18.43 1 32 0 0
#> 113.1 22.86 1 34 0 0
#> 23.1 16.92 1 61 0 0
#> 197 21.60 1 69 1 0
#> 63.1 22.77 1 31 1 0
#> 23.2 16.92 1 61 0 0
#> 93 10.33 1 52 0 1
#> 6.1 15.64 1 39 0 0
#> 180.1 14.82 1 37 0 0
#> 93.1 10.33 1 52 0 1
#> 15.1 22.68 1 48 0 0
#> 8.3 18.43 1 32 0 0
#> 97 19.14 1 65 0 1
#> 183.2 9.24 1 67 1 0
#> 92 22.92 1 47 0 1
#> 43 12.10 1 61 0 1
#> 157.1 15.10 1 47 0 0
#> 56 12.21 1 60 0 0
#> 183.3 9.24 1 67 1 0
#> 123.1 13.00 1 44 1 0
#> 139 21.49 1 63 1 0
#> 13.1 14.34 1 54 0 1
#> 69.3 23.23 1 25 0 1
#> 84 24.00 0 39 0 1
#> 174 24.00 0 49 1 0
#> 9 24.00 0 31 1 0
#> 64 24.00 0 43 0 0
#> 65 24.00 0 57 1 0
#> 48 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 112 24.00 0 61 0 0
#> 35 24.00 0 51 0 0
#> 28 24.00 0 67 1 0
#> 74 24.00 0 43 0 1
#> 47 24.00 0 38 0 1
#> 12 24.00 0 63 0 0
#> 95 24.00 0 68 0 1
#> 22 24.00 0 52 1 0
#> 98 24.00 0 34 1 0
#> 163 24.00 0 66 0 0
#> 198 24.00 0 66 0 1
#> 122.1 24.00 0 66 0 0
#> 11 24.00 0 42 0 1
#> 200 24.00 0 64 0 0
#> 182 24.00 0 35 0 0
#> 196 24.00 0 19 0 0
#> 186 24.00 0 45 1 0
#> 98.1 24.00 0 34 1 0
#> 185 24.00 0 44 1 0
#> 126 24.00 0 48 0 0
#> 9.1 24.00 0 31 1 0
#> 33 24.00 0 53 0 0
#> 135 24.00 0 58 1 0
#> 200.1 24.00 0 64 0 0
#> 198.1 24.00 0 66 0 1
#> 102 24.00 0 49 0 0
#> 38 24.00 0 31 1 0
#> 196.1 24.00 0 19 0 0
#> 28.1 24.00 0 67 1 0
#> 1 24.00 0 23 1 0
#> 198.2 24.00 0 66 0 1
#> 83 24.00 0 6 0 0
#> 98.2 24.00 0 34 1 0
#> 112.1 24.00 0 61 0 0
#> 17 24.00 0 38 0 1
#> 135.1 24.00 0 58 1 0
#> 71 24.00 0 51 0 0
#> 118 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 84.1 24.00 0 39 0 1
#> 74.1 24.00 0 43 0 1
#> 182.1 24.00 0 35 0 0
#> 137 24.00 0 45 1 0
#> 80 24.00 0 41 0 0
#> 147 24.00 0 76 1 0
#> 64.1 24.00 0 43 0 0
#> 22.1 24.00 0 52 1 0
#> 35.1 24.00 0 51 0 0
#> 174.1 24.00 0 49 1 0
#> 196.2 24.00 0 19 0 0
#> 54 24.00 0 53 1 0
#> 9.2 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 143 24.00 0 51 0 0
#> 83.1 24.00 0 6 0 0
#> 48.1 24.00 0 31 1 0
#> 112.2 24.00 0 61 0 0
#> 28.2 24.00 0 67 1 0
#> 83.2 24.00 0 6 0 0
#> 186.1 24.00 0 45 1 0
#> 193 24.00 0 45 0 1
#> 148 24.00 0 61 1 0
#> 135.2 24.00 0 58 1 0
#> 84.2 24.00 0 39 0 1
#> 178 24.00 0 52 1 0
#> 156 24.00 0 50 1 0
#> 191 24.00 0 60 0 1
#> 121 24.00 0 57 1 0
#> 162 24.00 0 51 0 0
#> 9.3 24.00 0 31 1 0
#> 65.1 24.00 0 57 1 0
#> 87 24.00 0 27 0 0
#> 46 24.00 0 71 0 0
#> 148.1 24.00 0 61 1 0
#> 48.2 24.00 0 31 1 0
#> 3 24.00 0 31 1 0
#> 144 24.00 0 28 0 1
#> 27 24.00 0 63 1 0
#> 35.2 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 162.1 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.0142 NA NA NA
#> 2 age, Cure model 0.00215 NA NA NA
#> 3 grade_ii, Cure model -0.388 NA NA NA
#> 4 grade_iii, Cure model 0.801 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00568 NA NA NA
#> 2 grade_ii, Survival model 0.653 NA NA NA
#> 3 grade_iii, Survival model 0.136 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.014200 0.002147 -0.387890 0.801130
#>
#> Degrees of Freedom: 194 Total (i.e. Null); 191 Residual
#> Null Deviance: 268.5
#> Residual Deviance: 258.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.014200031 0.002146869 -0.387889956 0.801130099
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.005677755 0.653133672 0.135991334
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.61981972 0.47828693 0.91473904 0.58774051 0.86562134 0.68029760
#> [7] 0.96174289 0.03007971 0.85926141 0.53858172 0.88445836 0.77934765
#> [13] 0.85284674 0.41332001 0.83990211 0.33720454 0.36006486 0.31367261
#> [19] 0.50478652 0.81325059 0.50478652 0.41332001 0.13736024 0.68029760
#> [25] 0.75868298 0.19497119 0.40345826 0.46002910 0.26258082 0.65818898
#> [31] 0.49601246 0.17836637 0.65818898 0.79979948 0.36006486 0.06734198
#> [37] 0.65818898 0.44127441 0.95024503 0.33720454 0.82665807 0.91473904
#> [43] 0.53005539 0.61188758 0.96174289 0.90272154 0.94437908 0.98365793
#> [49] 0.45069053 0.93850538 0.06734198 0.61981972 0.63536246 0.77245450
#> [55] 0.98914248 0.28957547 0.48717494 0.98914248 0.72372928 0.50478652
#> [61] 0.59585510 0.73094361 0.95024503 0.70931343 0.74485278 0.79298131
#> [67] 0.15886822 0.55540049 0.81999226 0.68029760 0.70203164 0.82665807
#> [73] 0.77934765 0.41332001 0.19497119 0.90874065 0.55540049 0.88445836
#> [79] 0.11408598 0.73094361 0.87195657 0.19497119 0.60389773 0.46002910
#> [85] 0.55540049 0.26258082 0.63536246 0.38242733 0.28957547 0.63536246
#> [91] 0.92666329 0.70931343 0.75868298 0.92666329 0.31367261 0.55540049
#> [97] 0.54703357 0.96174289 0.24840009 0.89663707 0.74485278 0.87821649
#> [103] 0.96174289 0.83990211 0.39318841 0.79979948 0.19497119 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 45 158 10 40 177 5 183 24 154 76 49 96 140
#> 17.42 20.14 10.53 18.00 12.53 16.43 9.24 23.89 12.63 19.22 12.19 14.54 12.68
#> 99 123 194 66 15 170 81 170.1 36 168 5.1 180 69
#> 21.19 13.00 22.40 22.13 22.68 19.54 14.06 19.54 21.19 23.72 16.43 14.82 23.23
#> 153 150 113 85 105 129 192 13 66.1 78 192.1 90 187
#> 21.33 20.33 22.86 16.44 19.75 23.41 16.44 14.34 22.13 23.88 16.44 20.94 9.92
#> 194.1 155 10.1 58 30 183.1 107 101 149 128 145 78.1 45.1
#> 22.40 13.08 10.53 19.34 17.43 9.24 11.18 9.97 8.37 20.35 10.07 23.88 17.42
#> 23 133 77 63 166 77.1 39 170.2 110 167 187.1 6 157
#> 16.92 14.65 7.27 22.77 19.98 7.27 15.59 19.54 17.56 15.55 9.92 15.64 15.10
#> 57 164 8 60 5.2 26 155.1 96.1 36.1 69.1 159 8.1 49.1
#> 14.46 23.60 18.43 13.15 16.43 15.77 13.08 14.54 21.19 23.23 10.55 18.43 12.19
#> 86 167.1 37 69.2 111 150.1 8.2 113.1 23.1 197 63.1 23.2 93
#> 23.81 15.55 12.52 23.23 17.45 20.33 18.43 22.86 16.92 21.60 22.77 16.92 10.33
#> 6.1 180.1 93.1 15.1 8.3 97 183.2 92 43 157.1 56 183.3 123.1
#> 15.64 14.82 10.33 22.68 18.43 19.14 9.24 22.92 12.10 15.10 12.21 9.24 13.00
#> 139 13.1 69.3 84 174 9 64 65 48 122 112 35 28
#> 21.49 14.34 23.23 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74 47 12 95 22 98 163 198 122.1 11 200 182 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 98.1 185 126 9.1 33 135 200.1 198.1 102 38 196.1 28.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 198.2 83 98.2 112.1 17 135.1 71 118 82 84.1 74.1 182.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 80 147 64.1 22.1 35.1 174.1 196.2 54 9.2 109 143 83.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48.1 112.2 28.2 83.2 186.1 193 148 135.2 84.2 178 156 191 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 9.3 65.1 87 46 148.1 48.2 3 144 27 35.2 19 162.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[2]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.004811865 0.763221736 0.931383550
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.64578243 0.02152967 -0.71620585
#> grade_iii, Cure model
#> 0.36846427
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 127 3.53 1 62 0 1
#> 192 16.44 1 31 1 0
#> 125 15.65 1 67 1 0
#> 129 23.41 1 53 1 0
#> 159 10.55 1 50 0 1
#> 39 15.59 1 37 0 1
#> 77 7.27 1 67 0 1
#> 13 14.34 1 54 0 1
#> 108 18.29 1 39 0 1
#> 49 12.19 1 48 1 0
#> 24 23.89 1 38 0 0
#> 188 16.16 1 46 0 1
#> 127.1 3.53 1 62 0 1
#> 184 17.77 1 38 0 0
#> 52 10.42 1 52 0 1
#> 175 21.91 1 43 0 0
#> 68 20.62 1 44 0 0
#> 56 12.21 1 60 0 0
#> 4 17.64 1 NA 0 1
#> 189 10.51 1 NA 1 0
#> 127.2 3.53 1 62 0 1
#> 183 9.24 1 67 1 0
#> 168 23.72 1 70 0 0
#> 78 23.88 1 43 0 0
#> 23 16.92 1 61 0 0
#> 41 18.02 1 40 1 0
#> 177 12.53 1 75 0 0
#> 136 21.83 1 43 0 1
#> 76 19.22 1 54 0 1
#> 85 16.44 1 36 0 0
#> 155 13.08 1 26 0 0
#> 85.1 16.44 1 36 0 0
#> 183.1 9.24 1 67 1 0
#> 43 12.10 1 61 0 1
#> 79 16.23 1 54 1 0
#> 188.1 16.16 1 46 0 1
#> 63 22.77 1 31 1 0
#> 57 14.46 1 45 0 1
#> 61 10.12 1 36 0 1
#> 140 12.68 1 59 1 0
#> 25 6.32 1 34 1 0
#> 195 11.76 1 NA 1 0
#> 139 21.49 1 63 1 0
#> 111 17.45 1 47 0 1
#> 111.1 17.45 1 47 0 1
#> 145 10.07 1 65 1 0
#> 175.1 21.91 1 43 0 0
#> 166 19.98 1 48 0 0
#> 113 22.86 1 34 0 0
#> 41.1 18.02 1 40 1 0
#> 57.1 14.46 1 45 0 1
#> 96 14.54 1 33 0 1
#> 86 23.81 1 58 0 1
#> 14 12.89 1 21 0 0
#> 167 15.55 1 56 1 0
#> 66 22.13 1 53 0 0
#> 99 21.19 1 38 0 1
#> 158 20.14 1 74 1 0
#> 91 5.33 1 61 0 1
#> 6 15.64 1 39 0 0
#> 49.1 12.19 1 48 1 0
#> 125.1 15.65 1 67 1 0
#> 111.2 17.45 1 47 0 1
#> 175.2 21.91 1 43 0 0
#> 159.1 10.55 1 50 0 1
#> 55 19.34 1 69 0 1
#> 61.1 10.12 1 36 0 1
#> 30 17.43 1 78 0 0
#> 60 13.15 1 38 1 0
#> 51 18.23 1 83 0 1
#> 81 14.06 1 34 0 0
#> 52.1 10.42 1 52 0 1
#> 57.2 14.46 1 45 0 1
#> 61.2 10.12 1 36 0 1
#> 63.1 22.77 1 31 1 0
#> 68.1 20.62 1 44 0 0
#> 88 18.37 1 47 0 0
#> 25.1 6.32 1 34 1 0
#> 117 17.46 1 26 0 1
#> 86.1 23.81 1 58 0 1
#> 128 20.35 1 35 0 1
#> 42 12.43 1 49 0 1
#> 187 9.92 1 39 1 0
#> 78.1 23.88 1 43 0 0
#> 59 10.16 1 NA 1 0
#> 97 19.14 1 65 0 1
#> 23.1 16.92 1 61 0 0
#> 59.1 10.16 1 NA 1 0
#> 91.1 5.33 1 61 0 1
#> 49.2 12.19 1 48 1 0
#> 14.1 12.89 1 21 0 0
#> 153 21.33 1 55 1 0
#> 59.2 10.16 1 NA 1 0
#> 114 13.68 1 NA 0 0
#> 89 11.44 1 NA 0 0
#> 97.1 19.14 1 65 0 1
#> 180 14.82 1 37 0 0
#> 43.1 12.10 1 61 0 1
#> 18 15.21 1 49 1 0
#> 78.2 23.88 1 43 0 0
#> 110 17.56 1 65 0 1
#> 190 20.81 1 42 1 0
#> 24.1 23.89 1 38 0 0
#> 41.2 18.02 1 40 1 0
#> 124 9.73 1 NA 1 0
#> 129.1 23.41 1 53 1 0
#> 89.1 11.44 1 NA 0 0
#> 24.2 23.89 1 38 0 0
#> 134 17.81 1 47 1 0
#> 96.1 14.54 1 33 0 1
#> 29 15.45 1 68 1 0
#> 145.1 10.07 1 65 1 0
#> 115 24.00 0 NA 1 0
#> 176 24.00 0 43 0 1
#> 196 24.00 0 19 0 0
#> 191 24.00 0 60 0 1
#> 120 24.00 0 68 0 1
#> 193 24.00 0 45 0 1
#> 94 24.00 0 51 0 1
#> 118 24.00 0 44 1 0
#> 72 24.00 0 40 0 1
#> 104 24.00 0 50 1 0
#> 152 24.00 0 36 0 1
#> 54 24.00 0 53 1 0
#> 126 24.00 0 48 0 0
#> 200 24.00 0 64 0 0
#> 87 24.00 0 27 0 0
#> 156 24.00 0 50 1 0
#> 72.1 24.00 0 40 0 1
#> 87.1 24.00 0 27 0 0
#> 35 24.00 0 51 0 0
#> 156.1 24.00 0 50 1 0
#> 162 24.00 0 51 0 0
#> 147 24.00 0 76 1 0
#> 20 24.00 0 46 1 0
#> 2 24.00 0 9 0 0
#> 82 24.00 0 34 0 0
#> 178 24.00 0 52 1 0
#> 83 24.00 0 6 0 0
#> 103 24.00 0 56 1 0
#> 146 24.00 0 63 1 0
#> 102 24.00 0 49 0 0
#> 73 24.00 0 NA 0 1
#> 7 24.00 0 37 1 0
#> 196.1 24.00 0 19 0 0
#> 144 24.00 0 28 0 1
#> 48 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 160 24.00 0 31 1 0
#> 38 24.00 0 31 1 0
#> 73.1 24.00 0 NA 0 1
#> 141 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 156.2 24.00 0 50 1 0
#> 73.2 24.00 0 NA 0 1
#> 135 24.00 0 58 1 0
#> 163 24.00 0 66 0 0
#> 33 24.00 0 53 0 0
#> 198 24.00 0 66 0 1
#> 27.1 24.00 0 63 1 0
#> 38.1 24.00 0 31 1 0
#> 11 24.00 0 42 0 1
#> 121 24.00 0 57 1 0
#> 185 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 27.2 24.00 0 63 1 0
#> 7.1 24.00 0 37 1 0
#> 146.1 24.00 0 63 1 0
#> 176.1 24.00 0 43 0 1
#> 48.1 24.00 0 31 1 0
#> 191.1 24.00 0 60 0 1
#> 176.2 24.00 0 43 0 1
#> 48.2 24.00 0 31 1 0
#> 148 24.00 0 61 1 0
#> 193.1 24.00 0 45 0 1
#> 62 24.00 0 71 0 0
#> 174 24.00 0 49 1 0
#> 148.1 24.00 0 61 1 0
#> 119 24.00 0 17 0 0
#> 137 24.00 0 45 1 0
#> 48.3 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 173 24.00 0 19 0 1
#> 178.1 24.00 0 52 1 0
#> 75 24.00 0 21 1 0
#> 67 24.00 0 25 0 0
#> 104.1 24.00 0 50 1 0
#> 67.1 24.00 0 25 0 0
#> 185.1 24.00 0 44 1 0
#> 20.1 24.00 0 46 1 0
#> 137.1 24.00 0 45 1 0
#> 27.3 24.00 0 63 1 0
#> 191.2 24.00 0 60 0 1
#> 141.1 24.00 0 44 1 0
#> 44 24.00 0 56 0 0
#> 44.1 24.00 0 56 0 0
#> 160.1 24.00 0 31 1 0
#> 174.1 24.00 0 49 1 0
#> 33.1 24.00 0 53 0 0
#> 94.1 24.00 0 51 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.646 NA NA NA
#> 2 age, Cure model 0.0215 NA NA NA
#> 3 grade_ii, Cure model -0.716 NA NA NA
#> 4 grade_iii, Cure model 0.368 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00481 NA NA NA
#> 2 grade_ii, Survival model 0.763 NA NA NA
#> 3 grade_iii, Survival model 0.931 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.64578 0.02153 -0.71621 0.36846
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.1
#> Residual Deviance: 243.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.64578243 0.02152967 -0.71620585 0.36846427
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.004811865 0.763221736 0.931383550
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.98832119 0.72936667 0.76734904 0.32839273 0.91536408 0.78522608
#> [7] 0.96793828 0.84054200 0.62126151 0.89149032 0.07686995 0.75506614
#> [13] 0.98832119 0.66787649 0.92457300 0.42156608 0.52365527 0.88650787
#> [19] 0.98832119 0.95954875 0.30774893 0.17679791 0.71622047 0.63776185
#> [25] 0.87646086 0.46289524 0.58605061 0.72936667 0.85604746 0.72936667
#> [31] 0.95954875 0.90594399 0.74867325 0.75506614 0.37801783 0.82485133
#> [37] 0.93357922 0.87139297 0.97209696 0.47623476 0.68974142 0.68974142
#> [43] 0.94667445 0.42156608 0.56621469 0.36130644 0.63776185 0.82485133
#> [49] 0.81390811 0.26678525 0.86117712 0.79110328 0.40697425 0.50099992
#> [55] 0.55603296 0.98028975 0.77925808 0.89149032 0.76734904 0.68974142
#> [61] 0.42156608 0.91536408 0.57634907 0.93357922 0.70957513 0.85091370
#> [67] 0.62966210 0.84573068 0.92457300 0.82485133 0.93357922 0.37801783
#> [73] 0.52365527 0.61262000 0.97209696 0.68261424 0.26678525 0.54545158
#> [79] 0.88151604 0.95527126 0.17679791 0.59539766 0.71622047 0.98028975
#> [85] 0.89149032 0.86117712 0.48889866 0.59539766 0.80826772 0.90594399
#> [91] 0.80261965 0.17679791 0.67534465 0.51253101 0.07686995 0.63776185
#> [97] 0.32839273 0.07686995 0.66039155 0.81390811 0.79690256 0.94667445
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 127 192 125 129 159 39 77 13 108 49 24 188 127.1
#> 3.53 16.44 15.65 23.41 10.55 15.59 7.27 14.34 18.29 12.19 23.89 16.16 3.53
#> 184 52 175 68 56 127.2 183 168 78 23 41 177 136
#> 17.77 10.42 21.91 20.62 12.21 3.53 9.24 23.72 23.88 16.92 18.02 12.53 21.83
#> 76 85 155 85.1 183.1 43 79 188.1 63 57 61 140 25
#> 19.22 16.44 13.08 16.44 9.24 12.10 16.23 16.16 22.77 14.46 10.12 12.68 6.32
#> 139 111 111.1 145 175.1 166 113 41.1 57.1 96 86 14 167
#> 21.49 17.45 17.45 10.07 21.91 19.98 22.86 18.02 14.46 14.54 23.81 12.89 15.55
#> 66 99 158 91 6 49.1 125.1 111.2 175.2 159.1 55 61.1 30
#> 22.13 21.19 20.14 5.33 15.64 12.19 15.65 17.45 21.91 10.55 19.34 10.12 17.43
#> 60 51 81 52.1 57.2 61.2 63.1 68.1 88 25.1 117 86.1 128
#> 13.15 18.23 14.06 10.42 14.46 10.12 22.77 20.62 18.37 6.32 17.46 23.81 20.35
#> 42 187 78.1 97 23.1 91.1 49.2 14.1 153 97.1 180 43.1 18
#> 12.43 9.92 23.88 19.14 16.92 5.33 12.19 12.89 21.33 19.14 14.82 12.10 15.21
#> 78.2 110 190 24.1 41.2 129.1 24.2 134 96.1 29 145.1 176 196
#> 23.88 17.56 20.81 23.89 18.02 23.41 23.89 17.81 14.54 15.45 10.07 24.00 24.00
#> 191 120 193 94 118 72 104 152 54 126 200 87 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.1 87.1 35 156.1 162 147 20 2 82 178 83 103 146
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 7 196.1 144 48 53 160 38 141 27 156.2 135 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 198 27.1 38.1 11 121 185 132 27.2 7.1 146.1 176.1 48.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191.1 176.2 48.2 148 193.1 62 174 148.1 119 137 48.3 21 173
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178.1 75 67 104.1 67.1 185.1 20.1 137.1 27.3 191.2 141.1 44 44.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160.1 174.1 33.1 94.1
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[3]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.004168651 0.391052875 0.336286128
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.568553324 0.009425192 0.339666260
#> grade_iii, Cure model
#> 0.714418263
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 197 21.60 1 69 1 0
#> 166 19.98 1 48 0 0
#> 188 16.16 1 46 0 1
#> 130 16.47 1 53 0 1
#> 123 13.00 1 44 1 0
#> 49 12.19 1 48 1 0
#> 18 15.21 1 49 1 0
#> 125 15.65 1 67 1 0
#> 125.1 15.65 1 67 1 0
#> 101 9.97 1 10 0 1
#> 92 22.92 1 47 0 1
#> 91 5.33 1 61 0 1
#> 55 19.34 1 69 0 1
#> 92.1 22.92 1 47 0 1
#> 106 16.67 1 49 1 0
#> 181 16.46 1 45 0 1
#> 55.1 19.34 1 69 0 1
#> 40 18.00 1 28 1 0
#> 61 10.12 1 36 0 1
#> 150 20.33 1 48 0 0
#> 100 16.07 1 60 0 0
#> 194 22.40 1 38 0 1
#> 166.1 19.98 1 48 0 0
#> 43 12.10 1 61 0 1
#> 6 15.64 1 39 0 0
#> 23 16.92 1 61 0 0
#> 124 9.73 1 NA 1 0
#> 181.1 16.46 1 45 0 1
#> 188.1 16.16 1 46 0 1
#> 77 7.27 1 67 0 1
#> 130.1 16.47 1 53 0 1
#> 166.2 19.98 1 48 0 0
#> 58 19.34 1 39 0 0
#> 63 22.77 1 31 1 0
#> 140 12.68 1 59 1 0
#> 169 22.41 1 46 0 0
#> 179 18.63 1 42 0 0
#> 101.1 9.97 1 10 0 1
#> 91.1 5.33 1 61 0 1
#> 42 12.43 1 49 0 1
#> 125.2 15.65 1 67 1 0
#> 113 22.86 1 34 0 0
#> 188.2 16.16 1 46 0 1
#> 63.1 22.77 1 31 1 0
#> 123.1 13.00 1 44 1 0
#> 63.2 22.77 1 31 1 0
#> 15 22.68 1 48 0 0
#> 190 20.81 1 42 1 0
#> 123.2 13.00 1 44 1 0
#> 127 3.53 1 62 0 1
#> 14 12.89 1 21 0 0
#> 194.1 22.40 1 38 0 1
#> 18.1 15.21 1 49 1 0
#> 68 20.62 1 44 0 0
#> 52 10.42 1 52 0 1
#> 61.1 10.12 1 36 0 1
#> 180 14.82 1 37 0 0
#> 134 17.81 1 47 1 0
#> 45 17.42 1 54 0 1
#> 99 21.19 1 38 0 1
#> 190.1 20.81 1 42 1 0
#> 136 21.83 1 43 0 1
#> 90 20.94 1 50 0 1
#> 124.1 9.73 1 NA 1 0
#> 91.2 5.33 1 61 0 1
#> 134.1 17.81 1 47 1 0
#> 69 23.23 1 25 0 1
#> 49.1 12.19 1 48 1 0
#> 134.2 17.81 1 47 1 0
#> 114 13.68 1 NA 0 0
#> 6.1 15.64 1 39 0 0
#> 77.1 7.27 1 67 0 1
#> 180.1 14.82 1 37 0 0
#> 78 23.88 1 43 0 0
#> 66 22.13 1 53 0 0
#> 113.1 22.86 1 34 0 0
#> 153 21.33 1 55 1 0
#> 10 10.53 1 34 0 0
#> 194.2 22.40 1 38 0 1
#> 157 15.10 1 47 0 0
#> 14.1 12.89 1 21 0 0
#> 130.2 16.47 1 53 0 1
#> 155 13.08 1 26 0 0
#> 57 14.46 1 45 0 1
#> 154 12.63 1 20 1 0
#> 26 15.77 1 49 0 1
#> 145 10.07 1 65 1 0
#> 187 9.92 1 39 1 0
#> 55.2 19.34 1 69 0 1
#> 5 16.43 1 51 0 1
#> 15.1 22.68 1 48 0 0
#> 14.2 12.89 1 21 0 0
#> 145.1 10.07 1 65 1 0
#> 29 15.45 1 68 1 0
#> 70 7.38 1 30 1 0
#> 166.3 19.98 1 48 0 0
#> 125.3 15.65 1 67 1 0
#> 130.3 16.47 1 53 0 1
#> 177 12.53 1 75 0 0
#> 43.1 12.10 1 61 0 1
#> 197.1 21.60 1 69 1 0
#> 168 23.72 1 70 0 0
#> 37 12.52 1 57 1 0
#> 105 19.75 1 60 0 0
#> 164 23.60 1 76 0 1
#> 50 10.02 1 NA 1 0
#> 16 8.71 1 71 0 1
#> 153.1 21.33 1 55 1 0
#> 63.3 22.77 1 31 1 0
#> 133 14.65 1 57 0 0
#> 51 18.23 1 83 0 1
#> 199 19.81 1 NA 0 1
#> 198 24.00 0 66 0 1
#> 98 24.00 0 34 1 0
#> 27 24.00 0 63 1 0
#> 53 24.00 0 32 0 1
#> 2 24.00 0 9 0 0
#> 137 24.00 0 45 1 0
#> 143 24.00 0 51 0 0
#> 143.1 24.00 0 51 0 0
#> 83 24.00 0 6 0 0
#> 103 24.00 0 56 1 0
#> 84 24.00 0 39 0 1
#> 44 24.00 0 56 0 0
#> 178 24.00 0 52 1 0
#> 126 24.00 0 48 0 0
#> 73 24.00 0 NA 0 1
#> 120 24.00 0 68 0 1
#> 54 24.00 0 53 1 0
#> 3 24.00 0 31 1 0
#> 132 24.00 0 55 0 0
#> 94 24.00 0 51 0 1
#> 9 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 163 24.00 0 66 0 0
#> 48 24.00 0 31 1 0
#> 143.2 24.00 0 51 0 0
#> 67 24.00 0 25 0 0
#> 182 24.00 0 35 0 0
#> 152 24.00 0 36 0 1
#> 185 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 200 24.00 0 64 0 0
#> 196 24.00 0 19 0 0
#> 147 24.00 0 76 1 0
#> 48.1 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 11 24.00 0 42 0 1
#> 122 24.00 0 66 0 0
#> 141 24.00 0 44 1 0
#> 53.1 24.00 0 32 0 1
#> 112 24.00 0 61 0 0
#> 83.1 24.00 0 6 0 0
#> 163.1 24.00 0 66 0 0
#> 95 24.00 0 68 0 1
#> 94.1 24.00 0 51 0 1
#> 38 24.00 0 31 1 0
#> 95.1 24.00 0 68 0 1
#> 44.1 24.00 0 56 0 0
#> 95.2 24.00 0 68 0 1
#> 34 24.00 0 36 0 0
#> 20 24.00 0 46 1 0
#> 31 24.00 0 36 0 1
#> 135 24.00 0 58 1 0
#> 163.2 24.00 0 66 0 0
#> 62 24.00 0 71 0 0
#> 11.1 24.00 0 42 0 1
#> 74 24.00 0 43 0 1
#> 28.1 24.00 0 67 1 0
#> 80.1 24.00 0 41 0 0
#> 54.1 24.00 0 53 1 0
#> 176 24.00 0 43 0 1
#> 156 24.00 0 50 1 0
#> 115 24.00 0 NA 1 0
#> 98.1 24.00 0 34 1 0
#> 131 24.00 0 66 0 0
#> 141.1 24.00 0 44 1 0
#> 196.1 24.00 0 19 0 0
#> 72 24.00 0 40 0 1
#> 64 24.00 0 43 0 0
#> 174 24.00 0 49 1 0
#> 83.2 24.00 0 6 0 0
#> 104 24.00 0 50 1 0
#> 165 24.00 0 47 0 0
#> 173 24.00 0 19 0 1
#> 94.2 24.00 0 51 0 1
#> 193 24.00 0 45 0 1
#> 152.1 24.00 0 36 0 1
#> 33 24.00 0 53 0 0
#> 27.1 24.00 0 63 1 0
#> 102 24.00 0 49 0 0
#> 17 24.00 0 38 0 1
#> 131.1 24.00 0 66 0 0
#> 165.1 24.00 0 47 0 0
#> 54.2 24.00 0 53 1 0
#> 82 24.00 0 34 0 0
#> 132.1 24.00 0 55 0 0
#> 119 24.00 0 17 0 0
#> 22 24.00 0 52 1 0
#> 173.1 24.00 0 19 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.569 NA NA NA
#> 2 age, Cure model 0.00943 NA NA NA
#> 3 grade_ii, Cure model 0.340 NA NA NA
#> 4 grade_iii, Cure model 0.714 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00417 NA NA NA
#> 2 grade_ii, Survival model 0.391 NA NA NA
#> 3 grade_iii, Survival model 0.336 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.568553 0.009425 0.339666 0.714418
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.3
#> Residual Deviance: 259.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.568553324 0.009425192 0.339666260 0.714418263
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.004168651 0.391052875 0.336286128
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.35313418 0.45353712 0.66191793 0.60873641 0.80121326 0.87286867
#> [7] 0.74702284 0.69849214 0.69849214 0.93494592 0.14064588 0.97682546
#> [13] 0.49926052 0.14064588 0.60066808 0.63919376 0.49926052 0.55125110
#> [19] 0.91048034 0.44397277 0.68382771 0.29502896 0.45353712 0.88550199
#> [25] 0.72616646 0.59251060 0.63919376 0.66191793 0.96503751 0.60873641
#> [31] 0.45353712 0.49926052 0.20629504 0.84046312 0.28197936 0.53376035
#> [37] 0.93494592 0.97682546 0.86645387 0.69849214 0.17393124 0.66191793
#> [43] 0.20629504 0.80121326 0.20629504 0.25623848 0.41527075 0.80121326
#> [49] 0.99420152 0.82085964 0.29502896 0.74702284 0.43436258 0.90425203
#> [55] 0.91048034 0.76743357 0.55983811 0.58432048 0.39506282 0.41527075
#> [61] 0.34153664 0.40525797 0.97682546 0.55983811 0.11908767 0.87286867
#> [67] 0.55983811 0.72616646 0.96503751 0.76743357 0.02780261 0.32966729
#> [73] 0.17393124 0.37460215 0.89799187 0.29502896 0.76061839 0.82085964
#> [79] 0.60873641 0.79448101 0.78774223 0.84700343 0.69118781 0.92278924
#> [85] 0.94703044 0.49926052 0.65435655 0.25623848 0.82085964 0.92278924
#> [91] 0.74009074 0.95906314 0.45353712 0.69849214 0.60873641 0.85351323
#> [97] 0.88550199 0.35313418 0.06413723 0.86000485 0.48994416 0.09515210
#> [103] 0.95306354 0.37460215 0.20629504 0.78096352 0.54257467 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000
#>
#> $Time
#> 197 166 188 130 123 49 18 125 125.1 101 92 91 55
#> 21.60 19.98 16.16 16.47 13.00 12.19 15.21 15.65 15.65 9.97 22.92 5.33 19.34
#> 92.1 106 181 55.1 40 61 150 100 194 166.1 43 6 23
#> 22.92 16.67 16.46 19.34 18.00 10.12 20.33 16.07 22.40 19.98 12.10 15.64 16.92
#> 181.1 188.1 77 130.1 166.2 58 63 140 169 179 101.1 91.1 42
#> 16.46 16.16 7.27 16.47 19.98 19.34 22.77 12.68 22.41 18.63 9.97 5.33 12.43
#> 125.2 113 188.2 63.1 123.1 63.2 15 190 123.2 127 14 194.1 18.1
#> 15.65 22.86 16.16 22.77 13.00 22.77 22.68 20.81 13.00 3.53 12.89 22.40 15.21
#> 68 52 61.1 180 134 45 99 190.1 136 90 91.2 134.1 69
#> 20.62 10.42 10.12 14.82 17.81 17.42 21.19 20.81 21.83 20.94 5.33 17.81 23.23
#> 49.1 134.2 6.1 77.1 180.1 78 66 113.1 153 10 194.2 157 14.1
#> 12.19 17.81 15.64 7.27 14.82 23.88 22.13 22.86 21.33 10.53 22.40 15.10 12.89
#> 130.2 155 57 154 26 145 187 55.2 5 15.1 14.2 145.1 29
#> 16.47 13.08 14.46 12.63 15.77 10.07 9.92 19.34 16.43 22.68 12.89 10.07 15.45
#> 70 166.3 125.3 130.3 177 43.1 197.1 168 37 105 164 16 153.1
#> 7.38 19.98 15.65 16.47 12.53 12.10 21.60 23.72 12.52 19.75 23.60 8.71 21.33
#> 63.3 133 51 198 98 27 53 2 137 143 143.1 83 103
#> 22.77 14.65 18.23 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 44 178 126 120 54 3 132 94 9 21 163 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143.2 67 182 152 185 80 200 196 147 48.1 28 11 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 53.1 112 83.1 163.1 95 94.1 38 95.1 44.1 95.2 34 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 135 163.2 62 11.1 74 28.1 80.1 54.1 176 156 98.1 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141.1 196.1 72 64 174 83.2 104 165 173 94.2 193 152.1 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27.1 102 17 131.1 165.1 54.2 82 132.1 119 22 173.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[4]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01632662 0.64737744 0.63293589
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.183232357 0.000561928 0.265419672
#> grade_iii, Cure model
#> 0.926240491
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 187 9.92 1 39 1 0
#> 139 21.49 1 63 1 0
#> 106 16.67 1 49 1 0
#> 91 5.33 1 61 0 1
#> 181 16.46 1 45 0 1
#> 90 20.94 1 50 0 1
#> 107 11.18 1 54 1 0
#> 184 17.77 1 38 0 0
#> 81 14.06 1 34 0 0
#> 89 11.44 1 NA 0 0
#> 14 12.89 1 21 0 0
#> 184.1 17.77 1 38 0 0
#> 145 10.07 1 65 1 0
#> 123 13.00 1 44 1 0
#> 150 20.33 1 48 0 0
#> 88 18.37 1 47 0 0
#> 50 10.02 1 NA 1 0
#> 108 18.29 1 39 0 1
#> 175 21.91 1 43 0 0
#> 192 16.44 1 31 1 0
#> 45 17.42 1 54 0 1
#> 188 16.16 1 46 0 1
#> 168 23.72 1 70 0 0
#> 52 10.42 1 52 0 1
#> 86 23.81 1 58 0 1
#> 101 9.97 1 10 0 1
#> 192.1 16.44 1 31 1 0
#> 63 22.77 1 31 1 0
#> 180 14.82 1 37 0 0
#> 171 16.57 1 41 0 1
#> 55 19.34 1 69 0 1
#> 63.1 22.77 1 31 1 0
#> 61 10.12 1 36 0 1
#> 66 22.13 1 53 0 0
#> 58 19.34 1 39 0 0
#> 145.1 10.07 1 65 1 0
#> 93 10.33 1 52 0 1
#> 78 23.88 1 43 0 0
#> 101.1 9.97 1 10 0 1
#> 199 19.81 1 NA 0 1
#> 15 22.68 1 48 0 0
#> 85 16.44 1 36 0 0
#> 195 11.76 1 NA 1 0
#> 88.1 18.37 1 47 0 0
#> 149 8.37 1 33 1 0
#> 157 15.10 1 47 0 0
#> 96 14.54 1 33 0 1
#> 123.1 13.00 1 44 1 0
#> 79 16.23 1 54 1 0
#> 197 21.60 1 69 1 0
#> 91.1 5.33 1 61 0 1
#> 180.1 14.82 1 37 0 0
#> 61.1 10.12 1 36 0 1
#> 40 18.00 1 28 1 0
#> 190 20.81 1 42 1 0
#> 76 19.22 1 54 0 1
#> 125 15.65 1 67 1 0
#> 86.1 23.81 1 58 0 1
#> 55.1 19.34 1 69 0 1
#> 189 10.51 1 NA 1 0
#> 110 17.56 1 65 0 1
#> 145.2 10.07 1 65 1 0
#> 52.1 10.42 1 52 0 1
#> 41 18.02 1 40 1 0
#> 133 14.65 1 57 0 0
#> 25 6.32 1 34 1 0
#> 25.1 6.32 1 34 1 0
#> 10 10.53 1 34 0 0
#> 4 17.64 1 NA 0 1
#> 43 12.10 1 61 0 1
#> 101.2 9.97 1 10 0 1
#> 58.1 19.34 1 39 0 0
#> 175.1 21.91 1 43 0 0
#> 175.2 21.91 1 43 0 0
#> 61.2 10.12 1 36 0 1
#> 68 20.62 1 44 0 0
#> 10.1 10.53 1 34 0 0
#> 133.1 14.65 1 57 0 0
#> 97 19.14 1 65 0 1
#> 97.1 19.14 1 65 0 1
#> 40.1 18.00 1 28 1 0
#> 187.1 9.92 1 39 1 0
#> 59 10.16 1 NA 1 0
#> 68.1 20.62 1 44 0 0
#> 68.2 20.62 1 44 0 0
#> 24 23.89 1 38 0 0
#> 170 19.54 1 43 0 1
#> 100 16.07 1 60 0 0
#> 188.1 16.16 1 46 0 1
#> 37 12.52 1 57 1 0
#> 110.1 17.56 1 65 0 1
#> 107.1 11.18 1 54 1 0
#> 96.1 14.54 1 33 0 1
#> 164 23.60 1 76 0 1
#> 100.1 16.07 1 60 0 0
#> 171.1 16.57 1 41 0 1
#> 39 15.59 1 37 0 1
#> 68.3 20.62 1 44 0 0
#> 77 7.27 1 67 0 1
#> 157.1 15.10 1 47 0 0
#> 170.1 19.54 1 43 0 1
#> 66.1 22.13 1 53 0 0
#> 14.1 12.89 1 21 0 0
#> 110.2 17.56 1 65 0 1
#> 127 3.53 1 62 0 1
#> 183 9.24 1 67 1 0
#> 170.2 19.54 1 43 0 1
#> 8 18.43 1 32 0 0
#> 187.2 9.92 1 39 1 0
#> 76.1 19.22 1 54 0 1
#> 39.1 15.59 1 37 0 1
#> 134 17.81 1 47 1 0
#> 31 24.00 0 36 0 1
#> 176 24.00 0 43 0 1
#> 17 24.00 0 38 0 1
#> 178 24.00 0 52 1 0
#> 193 24.00 0 45 0 1
#> 174 24.00 0 49 1 0
#> 35 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 174.1 24.00 0 49 1 0
#> 80 24.00 0 41 0 0
#> 131 24.00 0 66 0 0
#> 112 24.00 0 61 0 0
#> 94 24.00 0 51 0 1
#> 65 24.00 0 57 1 0
#> 135 24.00 0 58 1 0
#> 48 24.00 0 31 1 0
#> 35.1 24.00 0 51 0 0
#> 104 24.00 0 50 1 0
#> 65.1 24.00 0 57 1 0
#> 115 24.00 0 NA 1 0
#> 103 24.00 0 56 1 0
#> 71 24.00 0 51 0 0
#> 1 24.00 0 23 1 0
#> 27 24.00 0 63 1 0
#> 33 24.00 0 53 0 0
#> 104.1 24.00 0 50 1 0
#> 35.2 24.00 0 51 0 0
#> 71.1 24.00 0 51 0 0
#> 165 24.00 0 47 0 0
#> 109 24.00 0 48 0 0
#> 165.1 24.00 0 47 0 0
#> 53 24.00 0 32 0 1
#> 121 24.00 0 57 1 0
#> 84 24.00 0 39 0 1
#> 83 24.00 0 6 0 0
#> 87 24.00 0 27 0 0
#> 152 24.00 0 36 0 1
#> 82 24.00 0 34 0 0
#> 198 24.00 0 66 0 1
#> 21 24.00 0 47 0 0
#> 196 24.00 0 19 0 0
#> 147 24.00 0 76 1 0
#> 163 24.00 0 66 0 0
#> 185 24.00 0 44 1 0
#> 118 24.00 0 44 1 0
#> 109.1 24.00 0 48 0 0
#> 119 24.00 0 17 0 0
#> 64 24.00 0 43 0 0
#> 174.2 24.00 0 49 1 0
#> 83.1 24.00 0 6 0 0
#> 173 24.00 0 19 0 1
#> 120 24.00 0 68 0 1
#> 131.1 24.00 0 66 0 0
#> 141 24.00 0 44 1 0
#> 160 24.00 0 31 1 0
#> 12 24.00 0 63 0 0
#> 84.1 24.00 0 39 0 1
#> 62 24.00 0 71 0 0
#> 27.1 24.00 0 63 1 0
#> 132 24.00 0 55 0 0
#> 67 24.00 0 25 0 0
#> 146 24.00 0 63 1 0
#> 191 24.00 0 60 0 1
#> 165.2 24.00 0 47 0 0
#> 122 24.00 0 66 0 0
#> 173.1 24.00 0 19 0 1
#> 83.2 24.00 0 6 0 0
#> 162 24.00 0 51 0 0
#> 84.2 24.00 0 39 0 1
#> 44.1 24.00 0 56 0 0
#> 71.2 24.00 0 51 0 0
#> 185.1 24.00 0 44 1 0
#> 146.1 24.00 0 63 1 0
#> 165.3 24.00 0 47 0 0
#> 163.1 24.00 0 66 0 0
#> 196.1 24.00 0 19 0 0
#> 98 24.00 0 34 1 0
#> 11 24.00 0 42 0 1
#> 21.1 24.00 0 47 0 0
#> 103.1 24.00 0 56 1 0
#> 176.1 24.00 0 43 0 1
#> 7 24.00 0 37 1 0
#> 19 24.00 0 57 0 1
#> 151 24.00 0 42 0 0
#> 102 24.00 0 49 0 0
#> 109.2 24.00 0 48 0 0
#> 115.1 24.00 0 NA 1 0
#> 173.2 24.00 0 19 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.183 NA NA NA
#> 2 age, Cure model 0.000562 NA NA NA
#> 3 grade_ii, Cure model 0.265 NA NA NA
#> 4 grade_iii, Cure model 0.926 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0163 NA NA NA
#> 2 grade_ii, Survival model 0.647 NA NA NA
#> 3 grade_iii, Survival model 0.633 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.1832324 0.0005619 0.2654197 0.9262405
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 255.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.183232357 0.000561928 0.265419672 0.926240491
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01632662 0.64737744 0.63293589
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.8658629968 0.0598690886 0.3407492783 0.9630568587 0.3715755820
#> [6] 0.0663363004 0.6710658066 0.2811063089 0.5885475007 0.6235731040
#> [11] 0.2811063089 0.7927204714 0.6002784889 0.1069439764 0.2140622772
#> [16] 0.2331513640 0.0375876457 0.3819802090 0.3304306396 0.4229454138
#> [21] 0.0087520064 0.7193666888 0.0039253734 0.8297745601 0.3819802090
#> [26] 0.0168199806 0.5198404980 0.3511123585 0.1374265462 0.0168199806
#> [31] 0.7562444116 0.0281995938 0.1374265462 0.7927204714 0.7438568781
#> [36] 0.0014913517 0.8297745601 0.0239472199 0.3819802090 0.2140622772
#> [41] 0.9141833320 0.4977302939 0.5655129697 0.6002784889 0.4124667362
#> [46] 0.0536163953 0.9630568587 0.5198404980 0.7562444116 0.2526535252
#> [51] 0.0729113511 0.1695748318 0.4651961571 0.0039253734 0.1374265462
#> [56] 0.3006298494 0.7927204714 0.7193666888 0.2429013084 0.5423855734
#> [61] 0.9387011789 0.9387011789 0.6950374984 0.6590613805 0.8297745601
#> [66] 0.1374265462 0.0375876457 0.0375876457 0.7562444116 0.0795091725
#> [71] 0.6950374984 0.5423855734 0.1868740800 0.1868740800 0.2526535252
#> [76] 0.8658629968 0.0795091725 0.0795091725 0.0002322339 0.1148913706
#> [81] 0.4437567739 0.4229454138 0.6471231507 0.3006298494 0.6710658066
#> [86] 0.5655129697 0.0124877336 0.4437567739 0.3511123585 0.4761341392
#> [91] 0.0795091725 0.9264123001 0.4977302939 0.1148913706 0.0281995938
#> [96] 0.6235731040 0.3006298494 0.9876015162 0.9019355720 0.1148913706
#> [101] 0.2047506474 0.8658629968 0.1695748318 0.4761341392 0.2714836378
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [191] 0.0000000000
#>
#> $Time
#> 187 139 106 91 181 90 107 184 81 14 184.1 145 123
#> 9.92 21.49 16.67 5.33 16.46 20.94 11.18 17.77 14.06 12.89 17.77 10.07 13.00
#> 150 88 108 175 192 45 188 168 52 86 101 192.1 63
#> 20.33 18.37 18.29 21.91 16.44 17.42 16.16 23.72 10.42 23.81 9.97 16.44 22.77
#> 180 171 55 63.1 61 66 58 145.1 93 78 101.1 15 85
#> 14.82 16.57 19.34 22.77 10.12 22.13 19.34 10.07 10.33 23.88 9.97 22.68 16.44
#> 88.1 149 157 96 123.1 79 197 91.1 180.1 61.1 40 190 76
#> 18.37 8.37 15.10 14.54 13.00 16.23 21.60 5.33 14.82 10.12 18.00 20.81 19.22
#> 125 86.1 55.1 110 145.2 52.1 41 133 25 25.1 10 43 101.2
#> 15.65 23.81 19.34 17.56 10.07 10.42 18.02 14.65 6.32 6.32 10.53 12.10 9.97
#> 58.1 175.1 175.2 61.2 68 10.1 133.1 97 97.1 40.1 187.1 68.1 68.2
#> 19.34 21.91 21.91 10.12 20.62 10.53 14.65 19.14 19.14 18.00 9.92 20.62 20.62
#> 24 170 100 188.1 37 110.1 107.1 96.1 164 100.1 171.1 39 68.3
#> 23.89 19.54 16.07 16.16 12.52 17.56 11.18 14.54 23.60 16.07 16.57 15.59 20.62
#> 77 157.1 170.1 66.1 14.1 110.2 127 183 170.2 8 187.2 76.1 39.1
#> 7.27 15.10 19.54 22.13 12.89 17.56 3.53 9.24 19.54 18.43 9.92 19.22 15.59
#> 134 31 176 17 178 193 174 35 44 174.1 80 131 112
#> 17.81 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 65 135 48 35.1 104 65.1 103 71 1 27 33 104.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35.2 71.1 165 109 165.1 53 121 84 83 87 152 82 198
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 196 147 163 185 118 109.1 119 64 174.2 83.1 173 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.1 141 160 12 84.1 62 27.1 132 67 146 191 165.2 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173.1 83.2 162 84.2 44.1 71.2 185.1 146.1 165.3 163.1 196.1 98 11
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21.1 103.1 176.1 7 19 151 102 109.2 173.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[5]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003275168 0.857261310 0.769780600
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.303115069 0.009064013 0.307071042
#> grade_iii, Cure model
#> 0.047434530
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 77 7.27 1 67 0 1
#> 10 10.53 1 34 0 0
#> 171 16.57 1 41 0 1
#> 105 19.75 1 60 0 0
#> 133 14.65 1 57 0 0
#> 106 16.67 1 49 1 0
#> 79 16.23 1 54 1 0
#> 197 21.60 1 69 1 0
#> 59 10.16 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 56 12.21 1 60 0 0
#> 199 19.81 1 NA 0 1
#> 136 21.83 1 43 0 1
#> 88 18.37 1 47 0 0
#> 183 9.24 1 67 1 0
#> 49 12.19 1 48 1 0
#> 56.1 12.21 1 60 0 0
#> 68 20.62 1 44 0 0
#> 85 16.44 1 36 0 0
#> 113 22.86 1 34 0 0
#> 15 22.68 1 48 0 0
#> 52 10.42 1 52 0 1
#> 14 12.89 1 21 0 0
#> 55 19.34 1 69 0 1
#> 66 22.13 1 53 0 0
#> 66.1 22.13 1 53 0 0
#> 14.1 12.89 1 21 0 0
#> 167 15.55 1 56 1 0
#> 197.1 21.60 1 69 1 0
#> 76 19.22 1 54 0 1
#> 5 16.43 1 51 0 1
#> 29 15.45 1 68 1 0
#> 96 14.54 1 33 0 1
#> 93 10.33 1 52 0 1
#> 157 15.10 1 47 0 0
#> 181 16.46 1 45 0 1
#> 175 21.91 1 43 0 0
#> 24 23.89 1 38 0 0
#> 40 18.00 1 28 1 0
#> 52.1 10.42 1 52 0 1
#> 197.2 21.60 1 69 1 0
#> 139 21.49 1 63 1 0
#> 190 20.81 1 42 1 0
#> 96.1 14.54 1 33 0 1
#> 195 11.76 1 NA 1 0
#> 5.1 16.43 1 51 0 1
#> 111.1 17.45 1 47 0 1
#> 101 9.97 1 10 0 1
#> 105.1 19.75 1 60 0 0
#> 23 16.92 1 61 0 0
#> 60 13.15 1 38 1 0
#> 113.1 22.86 1 34 0 0
#> 150 20.33 1 48 0 0
#> 57 14.46 1 45 0 1
#> 153 21.33 1 55 1 0
#> 177 12.53 1 75 0 0
#> 40.1 18.00 1 28 1 0
#> 41 18.02 1 40 1 0
#> 145 10.07 1 65 1 0
#> 88.1 18.37 1 47 0 0
#> 166 19.98 1 48 0 0
#> 97 19.14 1 65 0 1
#> 42 12.43 1 49 0 1
#> 169 22.41 1 46 0 0
#> 89 11.44 1 NA 0 0
#> 49.1 12.19 1 48 1 0
#> 171.1 16.57 1 41 0 1
#> 76.1 19.22 1 54 0 1
#> 192 16.44 1 31 1 0
#> 25 6.32 1 34 1 0
#> 78 23.88 1 43 0 0
#> 58 19.34 1 39 0 0
#> 199.1 19.81 1 NA 0 1
#> 129 23.41 1 53 1 0
#> 123 13.00 1 44 1 0
#> 106.1 16.67 1 49 1 0
#> 37 12.52 1 57 1 0
#> 184 17.77 1 38 0 0
#> 168 23.72 1 70 0 0
#> 111.2 17.45 1 47 0 1
#> 42.1 12.43 1 49 0 1
#> 79.1 16.23 1 54 1 0
#> 6 15.64 1 39 0 0
#> 70 7.38 1 30 1 0
#> 192.1 16.44 1 31 1 0
#> 24.1 23.89 1 38 0 0
#> 91 5.33 1 61 0 1
#> 117 17.46 1 26 0 1
#> 25.1 6.32 1 34 1 0
#> 140 12.68 1 59 1 0
#> 180 14.82 1 37 0 0
#> 108 18.29 1 39 0 1
#> 13 14.34 1 54 0 1
#> 23.1 16.92 1 61 0 0
#> 159 10.55 1 50 0 1
#> 92 22.92 1 47 0 1
#> 167.1 15.55 1 56 1 0
#> 58.1 19.34 1 39 0 0
#> 179 18.63 1 42 0 0
#> 111.3 17.45 1 47 0 1
#> 188 16.16 1 46 0 1
#> 24.2 23.89 1 38 0 0
#> 166.1 19.98 1 48 0 0
#> 92.1 22.92 1 47 0 1
#> 69 23.23 1 25 0 1
#> 39 15.59 1 37 0 1
#> 29.1 15.45 1 68 1 0
#> 169.1 22.41 1 46 0 0
#> 106.2 16.67 1 49 1 0
#> 154 12.63 1 20 1 0
#> 154.1 12.63 1 20 1 0
#> 52.2 10.42 1 52 0 1
#> 109 24.00 0 48 0 0
#> 75 24.00 0 21 1 0
#> 1 24.00 0 23 1 0
#> 80 24.00 0 41 0 0
#> 80.1 24.00 0 41 0 0
#> 147 24.00 0 76 1 0
#> 95 24.00 0 68 0 1
#> 132 24.00 0 55 0 0
#> 151 24.00 0 42 0 0
#> 27 24.00 0 63 1 0
#> 200 24.00 0 64 0 0
#> 72 24.00 0 40 0 1
#> 116 24.00 0 58 0 1
#> 143 24.00 0 51 0 0
#> 11 24.00 0 42 0 1
#> 165 24.00 0 47 0 0
#> 84 24.00 0 39 0 1
#> 162 24.00 0 51 0 0
#> 35 24.00 0 51 0 0
#> 73 24.00 0 NA 0 1
#> 17 24.00 0 38 0 1
#> 84.1 24.00 0 39 0 1
#> 74 24.00 0 43 0 1
#> 178 24.00 0 52 1 0
#> 178.1 24.00 0 52 1 0
#> 193 24.00 0 45 0 1
#> 172 24.00 0 41 0 0
#> 191 24.00 0 60 0 1
#> 102 24.00 0 49 0 0
#> 53 24.00 0 32 0 1
#> 144 24.00 0 28 0 1
#> 2 24.00 0 9 0 0
#> 122 24.00 0 66 0 0
#> 34 24.00 0 36 0 0
#> 163 24.00 0 66 0 0
#> 31 24.00 0 36 0 1
#> 95.1 24.00 0 68 0 1
#> 118 24.00 0 44 1 0
#> 21 24.00 0 47 0 0
#> 84.2 24.00 0 39 0 1
#> 131 24.00 0 66 0 0
#> 172.1 24.00 0 41 0 0
#> 182 24.00 0 35 0 0
#> 148 24.00 0 61 1 0
#> 38 24.00 0 31 1 0
#> 72.1 24.00 0 40 0 1
#> 73.1 24.00 0 NA 0 1
#> 47 24.00 0 38 0 1
#> 87 24.00 0 27 0 0
#> 21.1 24.00 0 47 0 0
#> 11.1 24.00 0 42 0 1
#> 64 24.00 0 43 0 0
#> 178.2 24.00 0 52 1 0
#> 53.1 24.00 0 32 0 1
#> 2.1 24.00 0 9 0 0
#> 1.1 24.00 0 23 1 0
#> 65 24.00 0 57 1 0
#> 28 24.00 0 67 1 0
#> 82 24.00 0 34 0 0
#> 200.1 24.00 0 64 0 0
#> 9 24.00 0 31 1 0
#> 112 24.00 0 61 0 0
#> 144.1 24.00 0 28 0 1
#> 178.3 24.00 0 52 1 0
#> 152 24.00 0 36 0 1
#> 146 24.00 0 63 1 0
#> 35.1 24.00 0 51 0 0
#> 191.1 24.00 0 60 0 1
#> 72.2 24.00 0 40 0 1
#> 119 24.00 0 17 0 0
#> 53.2 24.00 0 32 0 1
#> 109.1 24.00 0 48 0 0
#> 156 24.00 0 50 1 0
#> 47.1 24.00 0 38 0 1
#> 146.1 24.00 0 63 1 0
#> 19 24.00 0 57 0 1
#> 11.2 24.00 0 42 0 1
#> 200.2 24.00 0 64 0 0
#> 120 24.00 0 68 0 1
#> 1.2 24.00 0 23 1 0
#> 176 24.00 0 43 0 1
#> 162.1 24.00 0 51 0 0
#> 28.1 24.00 0 67 1 0
#> 74.1 24.00 0 43 0 1
#> 87.1 24.00 0 27 0 0
#> 160 24.00 0 31 1 0
#> 9.1 24.00 0 31 1 0
#> 35.2 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.303 NA NA NA
#> 2 age, Cure model 0.00906 NA NA NA
#> 3 grade_ii, Cure model 0.307 NA NA NA
#> 4 grade_iii, Cure model 0.0474 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00328 NA NA NA
#> 2 grade_ii, Survival model 0.857 NA NA NA
#> 3 grade_iii, Survival model 0.770 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.303115 0.009064 0.307071 0.047435
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.3
#> Residual Deviance: 263.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.303115069 0.009064013 0.307071042 0.047434530
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003275168 0.857261310 0.769780600
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.97586012 0.91940151 0.63364960 0.38769766 0.77760536 0.60882287
#> [7] 0.69683651 0.27925134 0.55735882 0.88693193 0.26612829 0.48045358
#> [13] 0.96353172 0.90004025 0.88693193 0.34546332 0.65803466 0.16146351
#> [19] 0.18669366 0.92584996 0.82671612 0.40897852 0.22591274 0.22591274
#> [25] 0.82671612 0.73438674 0.27925134 0.44009658 0.68143733 0.74892535
#> [31] 0.78481419 0.94473906 0.76321810 0.64993068 0.25241331 0.01986803
#> [37] 0.52024183 0.92584996 0.27925134 0.31283695 0.33494930 0.78481419
#> [43] 0.68143733 0.55735882 0.95730962 0.38769766 0.59143826 0.81293886
#> [49] 0.16146351 0.35602049 0.79892360 0.32407564 0.86051850 0.52024183
#> [55] 0.51048656 0.95104313 0.48045358 0.36662341 0.46031413 0.87385809
#> [61] 0.19990129 0.90004025 0.63364960 0.44009658 0.65803466 0.98197381
#> [67] 0.06166055 0.40897852 0.10331741 0.81985760 0.60882287 0.86721280
#> [73] 0.53877758 0.08193546 0.55735882 0.87385809 0.69683651 0.71942010
#> [79] 0.96971818 0.65803466 0.01986803 0.99399773 0.54814559 0.98197381
#> [85] 0.84039128 0.77040789 0.50052818 0.80595589 0.59143826 0.91295783
#> [91] 0.13664897 0.73438674 0.40897852 0.47037000 0.55735882 0.71191103
#> [97] 0.01986803 0.36662341 0.13664897 0.12110907 0.72693858 0.74892535
#> [103] 0.19990129 0.60882287 0.84720444 0.84720444 0.92584996 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000
#>
#> $Time
#> 77 10 171 105 133 106 79 197 111 56 136 88 183
#> 7.27 10.53 16.57 19.75 14.65 16.67 16.23 21.60 17.45 12.21 21.83 18.37 9.24
#> 49 56.1 68 85 113 15 52 14 55 66 66.1 14.1 167
#> 12.19 12.21 20.62 16.44 22.86 22.68 10.42 12.89 19.34 22.13 22.13 12.89 15.55
#> 197.1 76 5 29 96 93 157 181 175 24 40 52.1 197.2
#> 21.60 19.22 16.43 15.45 14.54 10.33 15.10 16.46 21.91 23.89 18.00 10.42 21.60
#> 139 190 96.1 5.1 111.1 101 105.1 23 60 113.1 150 57 153
#> 21.49 20.81 14.54 16.43 17.45 9.97 19.75 16.92 13.15 22.86 20.33 14.46 21.33
#> 177 40.1 41 145 88.1 166 97 42 169 49.1 171.1 76.1 192
#> 12.53 18.00 18.02 10.07 18.37 19.98 19.14 12.43 22.41 12.19 16.57 19.22 16.44
#> 25 78 58 129 123 106.1 37 184 168 111.2 42.1 79.1 6
#> 6.32 23.88 19.34 23.41 13.00 16.67 12.52 17.77 23.72 17.45 12.43 16.23 15.64
#> 70 192.1 24.1 91 117 25.1 140 180 108 13 23.1 159 92
#> 7.38 16.44 23.89 5.33 17.46 6.32 12.68 14.82 18.29 14.34 16.92 10.55 22.92
#> 167.1 58.1 179 111.3 188 24.2 166.1 92.1 69 39 29.1 169.1 106.2
#> 15.55 19.34 18.63 17.45 16.16 23.89 19.98 22.92 23.23 15.59 15.45 22.41 16.67
#> 154 154.1 52.2 109 75 1 80 80.1 147 95 132 151 27
#> 12.63 12.63 10.42 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 72 116 143 11 165 84 162 35 17 84.1 74 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178.1 193 172 191 102 53 144 2 122 34 163 31 95.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 21 84.2 131 172.1 182 148 38 72.1 47 87 21.1 11.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 178.2 53.1 2.1 1.1 65 28 82 200.1 9 112 144.1 178.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 146 35.1 191.1 72.2 119 53.2 109.1 156 47.1 146.1 19 11.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200.2 120 1.2 176 162.1 28.1 74.1 87.1 160 9.1 35.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[6]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.009727393 0.114200127 0.544956793
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.54919094 0.02695659 0.56658166
#> grade_iii, Cure model
#> 0.72500753
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 51 18.23 1 83 0 1
#> 154 12.63 1 20 1 0
#> 189 10.51 1 NA 1 0
#> 170 19.54 1 43 0 1
#> 14 12.89 1 21 0 0
#> 13 14.34 1 54 0 1
#> 101 9.97 1 10 0 1
#> 199 19.81 1 NA 0 1
#> 15 22.68 1 48 0 0
#> 18 15.21 1 49 1 0
#> 187 9.92 1 39 1 0
#> 111 17.45 1 47 0 1
#> 8 18.43 1 32 0 0
#> 149 8.37 1 33 1 0
#> 114 13.68 1 NA 0 0
#> 42 12.43 1 49 0 1
#> 111.1 17.45 1 47 0 1
#> 170.1 19.54 1 43 0 1
#> 158 20.14 1 74 1 0
#> 78 23.88 1 43 0 0
#> 32 20.90 1 37 1 0
#> 77 7.27 1 67 0 1
#> 10 10.53 1 34 0 0
#> 180 14.82 1 37 0 0
#> 91 5.33 1 61 0 1
#> 107 11.18 1 54 1 0
#> 68 20.62 1 44 0 0
#> 78.1 23.88 1 43 0 0
#> 129 23.41 1 53 1 0
#> 45 17.42 1 54 0 1
#> 55 19.34 1 69 0 1
#> 157 15.10 1 47 0 0
#> 56 12.21 1 60 0 0
#> 85 16.44 1 36 0 0
#> 45.1 17.42 1 54 0 1
#> 129.1 23.41 1 53 1 0
#> 89 11.44 1 NA 0 0
#> 77.1 7.27 1 67 0 1
#> 51.1 18.23 1 83 0 1
#> 58 19.34 1 39 0 0
#> 167 15.55 1 56 1 0
#> 197 21.60 1 69 1 0
#> 37 12.52 1 57 1 0
#> 42.1 12.43 1 49 0 1
#> 26 15.77 1 49 0 1
#> 114.1 13.68 1 NA 0 0
#> 97 19.14 1 65 0 1
#> 91.1 5.33 1 61 0 1
#> 192 16.44 1 31 1 0
#> 149.1 8.37 1 33 1 0
#> 189.1 10.51 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 170.2 19.54 1 43 0 1
#> 16 8.71 1 71 0 1
#> 45.2 17.42 1 54 0 1
#> 123 13.00 1 44 1 0
#> 13.1 14.34 1 54 0 1
#> 197.1 21.60 1 69 1 0
#> 55.1 19.34 1 69 0 1
#> 129.2 23.41 1 53 1 0
#> 59 10.16 1 NA 1 0
#> 16.1 8.71 1 71 0 1
#> 41 18.02 1 40 1 0
#> 50 10.02 1 NA 1 0
#> 153 21.33 1 55 1 0
#> 194 22.40 1 38 0 1
#> 197.2 21.60 1 69 1 0
#> 107.1 11.18 1 54 1 0
#> 108 18.29 1 39 0 1
#> 167.1 15.55 1 56 1 0
#> 188 16.16 1 46 0 1
#> 55.2 19.34 1 69 0 1
#> 187.1 9.92 1 39 1 0
#> 15.1 22.68 1 48 0 0
#> 114.2 13.68 1 NA 0 0
#> 140 12.68 1 59 1 0
#> 101.1 9.97 1 10 0 1
#> 130 16.47 1 53 0 1
#> 140.1 12.68 1 59 1 0
#> 177 12.53 1 75 0 0
#> 66 22.13 1 53 0 0
#> 70 7.38 1 30 1 0
#> 6 15.64 1 39 0 0
#> 5 16.43 1 51 0 1
#> 77.2 7.27 1 67 0 1
#> 52 10.42 1 52 0 1
#> 61 10.12 1 36 0 1
#> 184 17.77 1 38 0 0
#> 23 16.92 1 61 0 0
#> 70.1 7.38 1 30 1 0
#> 194.1 22.40 1 38 0 1
#> 139 21.49 1 63 1 0
#> 23.1 16.92 1 61 0 0
#> 23.2 16.92 1 61 0 0
#> 129.3 23.41 1 53 1 0
#> 155 13.08 1 26 0 0
#> 59.1 10.16 1 NA 1 0
#> 157.1 15.10 1 47 0 0
#> 110 17.56 1 65 0 1
#> 190 20.81 1 42 1 0
#> 181 16.46 1 45 0 1
#> 5.1 16.43 1 51 0 1
#> 89.1 11.44 1 NA 0 0
#> 93 10.33 1 52 0 1
#> 96 14.54 1 33 0 1
#> 159 10.55 1 50 0 1
#> 129.4 23.41 1 53 1 0
#> 49 12.19 1 48 1 0
#> 92 22.92 1 47 0 1
#> 181.1 16.46 1 45 0 1
#> 52.1 10.42 1 52 0 1
#> 133 14.65 1 57 0 0
#> 186 24.00 0 45 1 0
#> 95 24.00 0 68 0 1
#> 35 24.00 0 51 0 0
#> 172 24.00 0 41 0 0
#> 151 24.00 0 42 0 0
#> 144 24.00 0 28 0 1
#> 122 24.00 0 66 0 0
#> 64 24.00 0 43 0 0
#> 19 24.00 0 57 0 1
#> 19.1 24.00 0 57 0 1
#> 109 24.00 0 48 0 0
#> 165 24.00 0 47 0 0
#> 84 24.00 0 39 0 1
#> 54 24.00 0 53 1 0
#> 75 24.00 0 21 1 0
#> 141 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 186.1 24.00 0 45 1 0
#> 152 24.00 0 36 0 1
#> 138 24.00 0 44 1 0
#> 121 24.00 0 57 1 0
#> 198 24.00 0 66 0 1
#> 193 24.00 0 45 0 1
#> 47 24.00 0 38 0 1
#> 7 24.00 0 37 1 0
#> 7.1 24.00 0 37 1 0
#> 35.1 24.00 0 51 0 0
#> 161 24.00 0 45 0 0
#> 67 24.00 0 25 0 0
#> 138.1 24.00 0 44 1 0
#> 115 24.00 0 NA 1 0
#> 94 24.00 0 51 0 1
#> 98 24.00 0 34 1 0
#> 115.1 24.00 0 NA 1 0
#> 116 24.00 0 58 0 1
#> 35.2 24.00 0 51 0 0
#> 131 24.00 0 66 0 0
#> 102 24.00 0 49 0 0
#> 141.1 24.00 0 44 1 0
#> 28 24.00 0 67 1 0
#> 80 24.00 0 41 0 0
#> 31 24.00 0 36 0 1
#> 47.1 24.00 0 38 0 1
#> 186.2 24.00 0 45 1 0
#> 94.1 24.00 0 51 0 1
#> 22 24.00 0 52 1 0
#> 67.1 24.00 0 25 0 0
#> 83 24.00 0 6 0 0
#> 193.1 24.00 0 45 0 1
#> 31.1 24.00 0 36 0 1
#> 152.1 24.00 0 36 0 1
#> 67.2 24.00 0 25 0 0
#> 172.1 24.00 0 41 0 0
#> 151.1 24.00 0 42 0 0
#> 65 24.00 0 57 1 0
#> 83.1 24.00 0 6 0 0
#> 75.1 24.00 0 21 1 0
#> 193.2 24.00 0 45 0 1
#> 121.1 24.00 0 57 1 0
#> 104 24.00 0 50 1 0
#> 74 24.00 0 43 0 1
#> 7.2 24.00 0 37 1 0
#> 193.3 24.00 0 45 0 1
#> 196 24.00 0 19 0 0
#> 156 24.00 0 50 1 0
#> 198.1 24.00 0 66 0 1
#> 109.1 24.00 0 48 0 0
#> 62 24.00 0 71 0 0
#> 87 24.00 0 27 0 0
#> 28.1 24.00 0 67 1 0
#> 53 24.00 0 32 0 1
#> 156.1 24.00 0 50 1 0
#> 62.1 24.00 0 71 0 0
#> 102.1 24.00 0 49 0 0
#> 193.4 24.00 0 45 0 1
#> 182 24.00 0 35 0 0
#> 87.1 24.00 0 27 0 0
#> 21 24.00 0 47 0 0
#> 82.1 24.00 0 34 0 0
#> 17 24.00 0 38 0 1
#> 191 24.00 0 60 0 1
#> 163 24.00 0 66 0 0
#> 152.2 24.00 0 36 0 1
#> 115.2 24.00 0 NA 1 0
#> 161.1 24.00 0 45 0 0
#> 116.1 24.00 0 58 0 1
#> 1 24.00 0 23 1 0
#> 80.1 24.00 0 41 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.55 NA NA NA
#> 2 age, Cure model 0.0270 NA NA NA
#> 3 grade_ii, Cure model 0.567 NA NA NA
#> 4 grade_iii, Cure model 0.725 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00973 NA NA NA
#> 2 grade_ii, Survival model 0.114 NA NA NA
#> 3 grade_iii, Survival model 0.545 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.54919 0.02696 0.56658 0.72501
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.5
#> Residual Deviance: 244.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.54919094 0.02695659 0.56658166 0.72500753
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.009727393 0.114200127 0.544956793
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.248410474 0.654488033 0.156922427 0.621083077 0.577263485 0.827145018
#> [7] 0.043443478 0.512052676 0.849895089 0.297582347 0.229055458 0.895762483
#> [13] 0.688540679 0.297582347 0.156922427 0.147237135 0.002735158 0.119625859
#> [19] 0.942027689 0.768953127 0.544304970 0.976711898 0.734174408 0.137832974
#> [25] 0.002735158 0.012497543 0.327314117 0.183608050 0.522769759 0.711157562
#> [31] 0.418192008 0.327314117 0.012497543 0.942027689 0.248410474 0.183608050
#> [37] 0.490975524 0.079032027 0.677111086 0.688540679 0.470057867 0.219451639
#> [43] 0.976711898 0.418192008 0.895762483 0.317186582 0.156922427 0.872787922
#> [49] 0.327314117 0.610015052 0.577263485 0.079032027 0.183608050 0.012497543
#> [55] 0.872787922 0.267659412 0.110750582 0.057789479 0.079032027 0.734174408
#> [61] 0.238768252 0.490975524 0.459618623 0.183608050 0.849895089 0.043443478
#> [67] 0.632187669 0.827145018 0.387243985 0.632187669 0.665749794 0.071503584
#> [73] 0.918847685 0.480480756 0.438929692 0.942027689 0.780648510 0.815508710
#> [79] 0.277550545 0.356715587 0.918847685 0.057789479 0.102113291 0.356715587
#> [85] 0.356715587 0.012497543 0.599000855 0.522769759 0.287551844 0.128647192
#> [91] 0.397691495 0.438929692 0.803836593 0.566282262 0.757307625 0.012497543
#> [97] 0.722638746 0.036514296 0.397691495 0.780648510 0.555247335 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 51 154 170 14 13 101 15 18 187 111 8 149 42
#> 18.23 12.63 19.54 12.89 14.34 9.97 22.68 15.21 9.92 17.45 18.43 8.37 12.43
#> 111.1 170.1 158 78 32 77 10 180 91 107 68 78.1 129
#> 17.45 19.54 20.14 23.88 20.90 7.27 10.53 14.82 5.33 11.18 20.62 23.88 23.41
#> 45 55 157 56 85 45.1 129.1 77.1 51.1 58 167 197 37
#> 17.42 19.34 15.10 12.21 16.44 17.42 23.41 7.27 18.23 19.34 15.55 21.60 12.52
#> 42.1 26 97 91.1 192 149.1 30 170.2 16 45.2 123 13.1 197.1
#> 12.43 15.77 19.14 5.33 16.44 8.37 17.43 19.54 8.71 17.42 13.00 14.34 21.60
#> 55.1 129.2 16.1 41 153 194 197.2 107.1 108 167.1 188 55.2 187.1
#> 19.34 23.41 8.71 18.02 21.33 22.40 21.60 11.18 18.29 15.55 16.16 19.34 9.92
#> 15.1 140 101.1 130 140.1 177 66 70 6 5 77.2 52 61
#> 22.68 12.68 9.97 16.47 12.68 12.53 22.13 7.38 15.64 16.43 7.27 10.42 10.12
#> 184 23 70.1 194.1 139 23.1 23.2 129.3 155 157.1 110 190 181
#> 17.77 16.92 7.38 22.40 21.49 16.92 16.92 23.41 13.08 15.10 17.56 20.81 16.46
#> 5.1 93 96 159 129.4 49 92 181.1 52.1 133 186 95 35
#> 16.43 10.33 14.54 10.55 23.41 12.19 22.92 16.46 10.42 14.65 24.00 24.00 24.00
#> 172 151 144 122 64 19 19.1 109 165 84 54 75 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82 186.1 152 138 121 198 193 47 7 7.1 35.1 161 67
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138.1 94 98 116 35.2 131 102 141.1 28 80 31 47.1 186.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.1 22 67.1 83 193.1 31.1 152.1 67.2 172.1 151.1 65 83.1 75.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193.2 121.1 104 74 7.2 193.3 196 156 198.1 109.1 62 87 28.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 156.1 62.1 102.1 193.4 182 87.1 21 82.1 17 191 163 152.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161.1 116.1 1 80.1
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[7]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.002596995 0.732392395 0.568584832
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.46622890 0.01524425 -0.60675070
#> grade_iii, Cure model
#> 0.35128091
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 26 15.77 1 49 0 1
#> 52 10.42 1 52 0 1
#> 187 9.92 1 39 1 0
#> 8 18.43 1 32 0 0
#> 99 21.19 1 38 0 1
#> 25 6.32 1 34 1 0
#> 180 14.82 1 37 0 0
#> 16 8.71 1 71 0 1
#> 36 21.19 1 48 0 1
#> 197 21.60 1 69 1 0
#> 88 18.37 1 47 0 0
#> 155 13.08 1 26 0 0
#> 23 16.92 1 61 0 0
#> 79 16.23 1 54 1 0
#> 111 17.45 1 47 0 1
#> 105 19.75 1 60 0 0
#> 58 19.34 1 39 0 0
#> 183 9.24 1 67 1 0
#> 99.1 21.19 1 38 0 1
#> 129 23.41 1 53 1 0
#> 192 16.44 1 31 1 0
#> 101 9.97 1 10 0 1
#> 153 21.33 1 55 1 0
#> 133 14.65 1 57 0 0
#> 108 18.29 1 39 0 1
#> 105.1 19.75 1 60 0 0
#> 171 16.57 1 41 0 1
#> 123 13.00 1 44 1 0
#> 66 22.13 1 53 0 0
#> 37 12.52 1 57 1 0
#> 195 11.76 1 NA 1 0
#> 24 23.89 1 38 0 0
#> 105.2 19.75 1 60 0 0
#> 155.1 13.08 1 26 0 0
#> 177 12.53 1 75 0 0
#> 129.1 23.41 1 53 1 0
#> 16.1 8.71 1 71 0 1
#> 169 22.41 1 46 0 0
#> 39 15.59 1 37 0 1
#> 25.1 6.32 1 34 1 0
#> 195.1 11.76 1 NA 1 0
#> 195.2 11.76 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 101.1 9.97 1 10 0 1
#> 50 10.02 1 NA 1 0
#> 155.2 13.08 1 26 0 0
#> 124 9.73 1 NA 1 0
#> 127 3.53 1 62 0 1
#> 128 20.35 1 35 0 1
#> 125 15.65 1 67 1 0
#> 13 14.34 1 54 0 1
#> 41 18.02 1 40 1 0
#> 183.1 9.24 1 67 1 0
#> 133.1 14.65 1 57 0 0
#> 194 22.40 1 38 0 1
#> 41.1 18.02 1 40 1 0
#> 24.1 23.89 1 38 0 0
#> 189 10.51 1 NA 1 0
#> 179 18.63 1 42 0 0
#> 13.1 14.34 1 54 0 1
#> 177.1 12.53 1 75 0 0
#> 56 12.21 1 60 0 0
#> 157 15.10 1 47 0 0
#> 154 12.63 1 20 1 0
#> 155.3 13.08 1 26 0 0
#> 55 19.34 1 69 0 1
#> 81 14.06 1 34 0 0
#> 96 14.54 1 33 0 1
#> 24.2 23.89 1 38 0 0
#> 50.1 10.02 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 166 19.98 1 48 0 0
#> 88.1 18.37 1 47 0 0
#> 10 10.53 1 34 0 0
#> 24.3 23.89 1 38 0 0
#> 128.1 20.35 1 35 0 1
#> 189.1 10.51 1 NA 1 0
#> 96.1 14.54 1 33 0 1
#> 49 12.19 1 48 1 0
#> 189.2 10.51 1 NA 1 0
#> 125.1 15.65 1 67 1 0
#> 49.1 12.19 1 48 1 0
#> 55.1 19.34 1 69 0 1
#> 128.2 20.35 1 35 0 1
#> 30.1 17.43 1 78 0 0
#> 86 23.81 1 58 0 1
#> 128.3 20.35 1 35 0 1
#> 136 21.83 1 43 0 1
#> 16.2 8.71 1 71 0 1
#> 159 10.55 1 50 0 1
#> 188 16.16 1 46 0 1
#> 45 17.42 1 54 0 1
#> 105.3 19.75 1 60 0 0
#> 14 12.89 1 21 0 0
#> 168.1 23.72 1 70 0 0
#> 93 10.33 1 52 0 1
#> 183.2 9.24 1 67 1 0
#> 52.1 10.42 1 52 0 1
#> 78 23.88 1 43 0 0
#> 37.1 12.52 1 57 1 0
#> 5 16.43 1 51 0 1
#> 167 15.55 1 56 1 0
#> 108.1 18.29 1 39 0 1
#> 113 22.86 1 34 0 0
#> 125.2 15.65 1 67 1 0
#> 158 20.14 1 74 1 0
#> 130 16.47 1 53 0 1
#> 150 20.33 1 48 0 0
#> 159.1 10.55 1 50 0 1
#> 23.1 16.92 1 61 0 0
#> 10.1 10.53 1 34 0 0
#> 78.1 23.88 1 43 0 0
#> 142 24.00 0 53 0 0
#> 148 24.00 0 61 1 0
#> 141 24.00 0 44 1 0
#> 22 24.00 0 52 1 0
#> 73 24.00 0 NA 0 1
#> 198 24.00 0 66 0 1
#> 109 24.00 0 48 0 0
#> 62 24.00 0 71 0 0
#> 118 24.00 0 44 1 0
#> 122 24.00 0 66 0 0
#> 138 24.00 0 44 1 0
#> 144 24.00 0 28 0 1
#> 98 24.00 0 34 1 0
#> 119 24.00 0 17 0 0
#> 1 24.00 0 23 1 0
#> 72 24.00 0 40 0 1
#> 156 24.00 0 50 1 0
#> 200 24.00 0 64 0 0
#> 151 24.00 0 42 0 0
#> 122.1 24.00 0 66 0 0
#> 84 24.00 0 39 0 1
#> 65 24.00 0 57 1 0
#> 80 24.00 0 41 0 0
#> 104 24.00 0 50 1 0
#> 103 24.00 0 56 1 0
#> 17 24.00 0 38 0 1
#> 143 24.00 0 51 0 0
#> 17.1 24.00 0 38 0 1
#> 172 24.00 0 41 0 0
#> 196 24.00 0 19 0 0
#> 33 24.00 0 53 0 0
#> 156.1 24.00 0 50 1 0
#> 95 24.00 0 68 0 1
#> 22.1 24.00 0 52 1 0
#> 141.1 24.00 0 44 1 0
#> 65.1 24.00 0 57 1 0
#> 103.1 24.00 0 56 1 0
#> 2 24.00 0 9 0 0
#> 176 24.00 0 43 0 1
#> 182 24.00 0 35 0 0
#> 162 24.00 0 51 0 0
#> 191 24.00 0 60 0 1
#> 182.1 24.00 0 35 0 0
#> 65.2 24.00 0 57 1 0
#> 141.2 24.00 0 44 1 0
#> 3 24.00 0 31 1 0
#> 2.1 24.00 0 9 0 0
#> 174 24.00 0 49 1 0
#> 138.1 24.00 0 44 1 0
#> 173 24.00 0 19 0 1
#> 31 24.00 0 36 0 1
#> 19 24.00 0 57 0 1
#> 172.1 24.00 0 41 0 0
#> 112 24.00 0 61 0 0
#> 138.2 24.00 0 44 1 0
#> 11 24.00 0 42 0 1
#> 72.1 24.00 0 40 0 1
#> 196.1 24.00 0 19 0 0
#> 142.1 24.00 0 53 0 0
#> 75 24.00 0 21 1 0
#> 27 24.00 0 63 1 0
#> 132 24.00 0 55 0 0
#> 34 24.00 0 36 0 0
#> 148.1 24.00 0 61 1 0
#> 191.1 24.00 0 60 0 1
#> 12 24.00 0 63 0 0
#> 119.1 24.00 0 17 0 0
#> 174.1 24.00 0 49 1 0
#> 144.1 24.00 0 28 0 1
#> 54 24.00 0 53 1 0
#> 102 24.00 0 49 0 0
#> 98.1 24.00 0 34 1 0
#> 46 24.00 0 71 0 0
#> 84.1 24.00 0 39 0 1
#> 165 24.00 0 47 0 0
#> 22.2 24.00 0 52 1 0
#> 53 24.00 0 32 0 1
#> 132.1 24.00 0 55 0 0
#> 174.2 24.00 0 49 1 0
#> 104.1 24.00 0 50 1 0
#> 144.2 24.00 0 28 0 1
#> 27.1 24.00 0 63 1 0
#> 163 24.00 0 66 0 0
#> 156.2 24.00 0 50 1 0
#> 152 24.00 0 36 0 1
#> 103.2 24.00 0 56 1 0
#> 131 24.00 0 66 0 0
#> 19.1 24.00 0 57 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.466 NA NA NA
#> 2 age, Cure model 0.0152 NA NA NA
#> 3 grade_ii, Cure model -0.607 NA NA NA
#> 4 grade_iii, Cure model 0.351 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00260 NA NA NA
#> 2 grade_ii, Survival model 0.732 NA NA NA
#> 3 grade_iii, Survival model 0.569 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.46623 0.01524 -0.60675 0.35128
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 254.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.46622890 0.01524425 -0.60675070 0.35128091
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.002596995 0.732392395 0.568584832
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.69321828 0.91318557 0.94329662 0.53477127 0.35849664 0.98333148
#> [7] 0.74305629 0.96645024 0.35849664 0.33271809 0.54396249 0.79762300
#> [13] 0.62989557 0.67797015 0.59665044 0.46088840 0.49837851 0.94923117
#> [19] 0.35849664 0.22744128 0.66229968 0.93136747 0.34594310 0.75003729
#> [25] 0.56211074 0.46088840 0.64619558 0.82408882 0.30397438 0.85692688
#> [31] 0.05066014 0.46088840 0.79762300 0.84389892 0.22744128 0.96645024
#> [37] 0.27363469 0.72198051 0.98333148 0.18994903 0.93136747 0.79762300
#> [43] 0.99445567 0.39161461 0.70071791 0.77752111 0.57971682 0.94923117
#> [49] 0.75003729 0.28918168 0.57971682 0.05066014 0.52556634 0.77752111
#> [55] 0.84389892 0.86968107 0.73606866 0.83733775 0.79762300 0.49837851
#> [61] 0.79090684 0.76389337 0.05066014 0.60505862 0.45107719 0.54396249
#> [67] 0.90088366 0.05066014 0.39161461 0.76389337 0.87607379 0.70071791
#> [73] 0.87607379 0.49837851 0.39161461 0.60505862 0.16933276 0.39161461
#> [79] 0.31866176 0.96645024 0.88856623 0.68563617 0.62165532 0.46088840
#> [85] 0.83071476 0.18994903 0.92532057 0.94923117 0.91318557 0.12535713
#> [91] 0.85692688 0.67018144 0.72907242 0.56211074 0.25797508 0.70071791
#> [97] 0.44123757 0.65429848 0.43105257 0.88856623 0.62989557 0.90088366
#> [103] 0.12535713 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 26 52 187 8 99 25 180 16 36 197 88 155 23
#> 15.77 10.42 9.92 18.43 21.19 6.32 14.82 8.71 21.19 21.60 18.37 13.08 16.92
#> 79 111 105 58 183 99.1 129 192 101 153 133 108 105.1
#> 16.23 17.45 19.75 19.34 9.24 21.19 23.41 16.44 9.97 21.33 14.65 18.29 19.75
#> 171 123 66 37 24 105.2 155.1 177 129.1 16.1 169 39 25.1
#> 16.57 13.00 22.13 12.52 23.89 19.75 13.08 12.53 23.41 8.71 22.41 15.59 6.32
#> 168 101.1 155.2 127 128 125 13 41 183.1 133.1 194 41.1 24.1
#> 23.72 9.97 13.08 3.53 20.35 15.65 14.34 18.02 9.24 14.65 22.40 18.02 23.89
#> 179 13.1 177.1 56 157 154 155.3 55 81 96 24.2 30 166
#> 18.63 14.34 12.53 12.21 15.10 12.63 13.08 19.34 14.06 14.54 23.89 17.43 19.98
#> 88.1 10 24.3 128.1 96.1 49 125.1 49.1 55.1 128.2 30.1 86 128.3
#> 18.37 10.53 23.89 20.35 14.54 12.19 15.65 12.19 19.34 20.35 17.43 23.81 20.35
#> 136 16.2 159 188 45 105.3 14 168.1 93 183.2 52.1 78 37.1
#> 21.83 8.71 10.55 16.16 17.42 19.75 12.89 23.72 10.33 9.24 10.42 23.88 12.52
#> 5 167 108.1 113 125.2 158 130 150 159.1 23.1 10.1 78.1 142
#> 16.43 15.55 18.29 22.86 15.65 20.14 16.47 20.33 10.55 16.92 10.53 23.88 24.00
#> 148 141 22 198 109 62 118 122 138 144 98 119 1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72 156 200 151 122.1 84 65 80 104 103 17 143 17.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172 196 33 156.1 95 22.1 141.1 65.1 103.1 2 176 182 162
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191 182.1 65.2 141.2 3 2.1 174 138.1 173 31 19 172.1 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138.2 11 72.1 196.1 142.1 75 27 132 34 148.1 191.1 12 119.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174.1 144.1 54 102 98.1 46 84.1 165 22.2 53 132.1 174.2 104.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144.2 27.1 163 156.2 152 103.2 131 19.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[8]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01990538 0.42924337 0.43090361
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.94283259 0.01548236 0.22930188
#> grade_iii, Cure model
#> 0.92622719
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 81 14.06 1 34 0 0
#> 157 15.10 1 47 0 0
#> 129 23.41 1 53 1 0
#> 86 23.81 1 58 0 1
#> 61 10.12 1 36 0 1
#> 180 14.82 1 37 0 0
#> 164 23.60 1 76 0 1
#> 158 20.14 1 74 1 0
#> 51 18.23 1 83 0 1
#> 167 15.55 1 56 1 0
#> 68 20.62 1 44 0 0
#> 124 9.73 1 NA 1 0
#> 29 15.45 1 68 1 0
#> 92 22.92 1 47 0 1
#> 108 18.29 1 39 0 1
#> 168 23.72 1 70 0 0
#> 154 12.63 1 20 1 0
#> 90 20.94 1 50 0 1
#> 159 10.55 1 50 0 1
#> 100 16.07 1 60 0 0
#> 88 18.37 1 47 0 0
#> 158.1 20.14 1 74 1 0
#> 50 10.02 1 NA 1 0
#> 18 15.21 1 49 1 0
#> 157.1 15.10 1 47 0 0
#> 110 17.56 1 65 0 1
#> 86.1 23.81 1 58 0 1
#> 36 21.19 1 48 0 1
#> 76 19.22 1 54 0 1
#> 61.1 10.12 1 36 0 1
#> 77 7.27 1 67 0 1
#> 158.2 20.14 1 74 1 0
#> 61.2 10.12 1 36 0 1
#> 190 20.81 1 42 1 0
#> 130 16.47 1 53 0 1
#> 61.3 10.12 1 36 0 1
#> 24 23.89 1 38 0 0
#> 197 21.60 1 69 1 0
#> 18.1 15.21 1 49 1 0
#> 10 10.53 1 34 0 0
#> 25 6.32 1 34 1 0
#> 197.1 21.60 1 69 1 0
#> 61.4 10.12 1 36 0 1
#> 154.1 12.63 1 20 1 0
#> 60 13.15 1 38 1 0
#> 89 11.44 1 NA 0 0
#> 89.1 11.44 1 NA 0 0
#> 175 21.91 1 43 0 0
#> 85 16.44 1 36 0 0
#> 45 17.42 1 54 0 1
#> 77.1 7.27 1 67 0 1
#> 129.1 23.41 1 53 1 0
#> 89.2 11.44 1 NA 0 0
#> 40 18.00 1 28 1 0
#> 70 7.38 1 30 1 0
#> 81.1 14.06 1 34 0 0
#> 153 21.33 1 55 1 0
#> 111 17.45 1 47 0 1
#> 177 12.53 1 75 0 0
#> 92.1 22.92 1 47 0 1
#> 149 8.37 1 33 1 0
#> 60.1 13.15 1 38 1 0
#> 197.2 21.60 1 69 1 0
#> 32 20.90 1 37 1 0
#> 51.1 18.23 1 83 0 1
#> 192 16.44 1 31 1 0
#> 30 17.43 1 78 0 0
#> 100.1 16.07 1 60 0 0
#> 170 19.54 1 43 0 1
#> 14 12.89 1 21 0 0
#> 50.1 10.02 1 NA 1 0
#> 16 8.71 1 71 0 1
#> 66 22.13 1 53 0 0
#> 78 23.88 1 43 0 0
#> 124.1 9.73 1 NA 1 0
#> 179 18.63 1 42 0 0
#> 171 16.57 1 41 0 1
#> 123 13.00 1 44 1 0
#> 13 14.34 1 54 0 1
#> 154.2 12.63 1 20 1 0
#> 24.1 23.89 1 38 0 0
#> 51.2 18.23 1 83 0 1
#> 91 5.33 1 61 0 1
#> 92.2 22.92 1 47 0 1
#> 155 13.08 1 26 0 0
#> 159.1 10.55 1 50 0 1
#> 92.3 22.92 1 47 0 1
#> 30.1 17.43 1 78 0 0
#> 181 16.46 1 45 0 1
#> 49 12.19 1 48 1 0
#> 192.1 16.44 1 31 1 0
#> 13.1 14.34 1 54 0 1
#> 197.3 21.60 1 69 1 0
#> 189 10.51 1 NA 1 0
#> 81.2 14.06 1 34 0 0
#> 61.5 10.12 1 36 0 1
#> 153.1 21.33 1 55 1 0
#> 130.1 16.47 1 53 0 1
#> 88.1 18.37 1 47 0 0
#> 192.2 16.44 1 31 1 0
#> 40.1 18.00 1 28 1 0
#> 76.1 19.22 1 54 0 1
#> 117 17.46 1 26 0 1
#> 106 16.67 1 49 1 0
#> 97 19.14 1 65 0 1
#> 57 14.46 1 45 0 1
#> 127 3.53 1 62 0 1
#> 157.2 15.10 1 47 0 0
#> 189.1 10.51 1 NA 1 0
#> 15 22.68 1 48 0 0
#> 45.1 17.42 1 54 0 1
#> 179.1 18.63 1 42 0 0
#> 72 24.00 0 40 0 1
#> 160 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 132 24.00 0 55 0 0
#> 135 24.00 0 58 1 0
#> 80.1 24.00 0 41 0 0
#> 95 24.00 0 68 0 1
#> 2 24.00 0 9 0 0
#> 71 24.00 0 51 0 0
#> 165 24.00 0 47 0 0
#> 144 24.00 0 28 0 1
#> 21 24.00 0 47 0 0
#> 72.1 24.00 0 40 0 1
#> 17 24.00 0 38 0 1
#> 103 24.00 0 56 1 0
#> 196 24.00 0 19 0 0
#> 84 24.00 0 39 0 1
#> 102 24.00 0 49 0 0
#> 74 24.00 0 43 0 1
#> 198 24.00 0 66 0 1
#> 132.1 24.00 0 55 0 0
#> 87 24.00 0 27 0 0
#> 198.1 24.00 0 66 0 1
#> 48 24.00 0 31 1 0
#> 144.1 24.00 0 28 0 1
#> 82 24.00 0 34 0 0
#> 137 24.00 0 45 1 0
#> 98 24.00 0 34 1 0
#> 83 24.00 0 6 0 0
#> 178 24.00 0 52 1 0
#> 131 24.00 0 66 0 0
#> 162 24.00 0 51 0 0
#> 46 24.00 0 71 0 0
#> 109 24.00 0 48 0 0
#> 156 24.00 0 50 1 0
#> 121 24.00 0 57 1 0
#> 94 24.00 0 51 0 1
#> 173 24.00 0 19 0 1
#> 148 24.00 0 61 1 0
#> 1 24.00 0 23 1 0
#> 182 24.00 0 35 0 0
#> 162.1 24.00 0 51 0 0
#> 185.1 24.00 0 44 1 0
#> 186 24.00 0 45 1 0
#> 62 24.00 0 71 0 0
#> 34 24.00 0 36 0 0
#> 144.2 24.00 0 28 0 1
#> 47 24.00 0 38 0 1
#> 172 24.00 0 41 0 0
#> 9 24.00 0 31 1 0
#> 87.1 24.00 0 27 0 0
#> 163 24.00 0 66 0 0
#> 186.1 24.00 0 45 1 0
#> 112 24.00 0 61 0 0
#> 9.1 24.00 0 31 1 0
#> 137.1 24.00 0 45 1 0
#> 148.1 24.00 0 61 1 0
#> 47.1 24.00 0 38 0 1
#> 112.1 24.00 0 61 0 0
#> 126 24.00 0 48 0 0
#> 121.1 24.00 0 57 1 0
#> 102.1 24.00 0 49 0 0
#> 28 24.00 0 67 1 0
#> 1.1 24.00 0 23 1 0
#> 102.2 24.00 0 49 0 0
#> 122 24.00 0 66 0 0
#> 132.2 24.00 0 55 0 0
#> 120 24.00 0 68 0 1
#> 148.2 24.00 0 61 1 0
#> 94.1 24.00 0 51 0 1
#> 103.1 24.00 0 56 1 0
#> 28.1 24.00 0 67 1 0
#> 75 24.00 0 21 1 0
#> 200 24.00 0 64 0 0
#> 196.1 24.00 0 19 0 0
#> 160.1 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 160.2 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 53 24.00 0 32 0 1
#> 172.1 24.00 0 41 0 0
#> 132.3 24.00 0 55 0 0
#> 148.3 24.00 0 61 1 0
#> 72.2 24.00 0 40 0 1
#> 160.3 24.00 0 31 1 0
#> 174.1 24.00 0 49 1 0
#> 103.2 24.00 0 56 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.943 NA NA NA
#> 2 age, Cure model 0.0155 NA NA NA
#> 3 grade_ii, Cure model 0.229 NA NA NA
#> 4 grade_iii, Cure model 0.926 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0199 NA NA NA
#> 2 grade_ii, Survival model 0.429 NA NA NA
#> 3 grade_iii, Survival model 0.431 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.94283 0.01548 0.22930 0.92623
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.6
#> Residual Deviance: 253.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.94283259 0.01548236 0.22930188 0.92622719
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01990538 0.42924337 0.43090361
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 5.262297e-01 4.316304e-01 5.305451e-03 1.085442e-03 7.681038e-01
#> [6] 4.708393e-01 3.767304e-03 7.146460e-02 1.509202e-01 3.818379e-01
#> [11] 6.622205e-02 3.940473e-01 8.757626e-03 1.430482e-01 2.557516e-03
#> [16] 6.443143e-01 5.156563e-02 7.203501e-01 3.581787e-01 1.279729e-01
#> [21] 7.146460e-02 4.064893e-01 4.316304e-01 1.932599e-01 1.085442e-03
#> [26] 4.698062e-02 9.445739e-02 7.681038e-01 9.133218e-01 7.146460e-02
#> [31] 7.681038e-01 6.121105e-02 2.816162e-01 7.681038e-01 6.191623e-05
#> [36] 2.487811e-02 4.064893e-01 7.519604e-01 9.475156e-01 2.487811e-02
#> [41] 7.681038e-01 6.443143e-01 5.692392e-01 2.179689e-02 3.143718e-01
#> [46] 2.402475e-01 9.133218e-01 5.305451e-03 1.759481e-01 8.964412e-01
#> [51] 5.262297e-01 3.857608e-02 2.114942e-01 6.891272e-01 8.757626e-03
#> [56] 8.796096e-01 5.692392e-01 2.487811e-02 5.633364e-02 1.509202e-01
#> [61] 3.143718e-01 2.207875e-01 3.581787e-01 8.830023e-02 6.289822e-01
#> [66] 8.628434e-01 1.894758e-02 5.213303e-04 1.139053e-01 2.709854e-01
#> [71] 6.137768e-01 4.982909e-01 6.443143e-01 6.191623e-05 1.509202e-01
#> [76] 9.648388e-01 8.757626e-03 5.987059e-01 7.203501e-01 8.757626e-03
#> [81] 2.207875e-01 3.032199e-01 7.046679e-01 3.143718e-01 4.982909e-01
#> [86] 2.487811e-02 5.262297e-01 7.681038e-01 3.857608e-02 2.816162e-01
#> [91] 1.279729e-01 3.143718e-01 1.759481e-01 9.445739e-02 2.023600e-01
#> [96] 2.604863e-01 1.071304e-01 4.844928e-01 9.823325e-01 4.316304e-01
#> [101] 1.635283e-02 2.402475e-01 1.139053e-01 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [191] 0.000000e+00
#>
#> $Time
#> 81 157 129 86 61 180 164 158 51 167 68 29 92
#> 14.06 15.10 23.41 23.81 10.12 14.82 23.60 20.14 18.23 15.55 20.62 15.45 22.92
#> 108 168 154 90 159 100 88 158.1 18 157.1 110 86.1 36
#> 18.29 23.72 12.63 20.94 10.55 16.07 18.37 20.14 15.21 15.10 17.56 23.81 21.19
#> 76 61.1 77 158.2 61.2 190 130 61.3 24 197 18.1 10 25
#> 19.22 10.12 7.27 20.14 10.12 20.81 16.47 10.12 23.89 21.60 15.21 10.53 6.32
#> 197.1 61.4 154.1 60 175 85 45 77.1 129.1 40 70 81.1 153
#> 21.60 10.12 12.63 13.15 21.91 16.44 17.42 7.27 23.41 18.00 7.38 14.06 21.33
#> 111 177 92.1 149 60.1 197.2 32 51.1 192 30 100.1 170 14
#> 17.45 12.53 22.92 8.37 13.15 21.60 20.90 18.23 16.44 17.43 16.07 19.54 12.89
#> 16 66 78 179 171 123 13 154.2 24.1 51.2 91 92.2 155
#> 8.71 22.13 23.88 18.63 16.57 13.00 14.34 12.63 23.89 18.23 5.33 22.92 13.08
#> 159.1 92.3 30.1 181 49 192.1 13.1 197.3 81.2 61.5 153.1 130.1 88.1
#> 10.55 22.92 17.43 16.46 12.19 16.44 14.34 21.60 14.06 10.12 21.33 16.47 18.37
#> 192.2 40.1 76.1 117 106 97 57 127 157.2 15 45.1 179.1 72
#> 16.44 18.00 19.22 17.46 16.67 19.14 14.46 3.53 15.10 22.68 17.42 18.63 24.00
#> 160 185 80 132 135 80.1 95 2 71 165 144 21 72.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17 103 196 84 102 74 198 132.1 87 198.1 48 144.1 82
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 98 83 178 131 162 46 109 156 121 94 173 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 182 162.1 185.1 186 62 34 144.2 47 172 9 87.1 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186.1 112 9.1 137.1 148.1 47.1 112.1 126 121.1 102.1 28 1.1 102.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 132.2 120 148.2 94.1 103.1 28.1 75 200 196.1 160.1 174 160.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 53 172.1 132.3 148.3 72.2 160.3 174.1 103.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[9]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.005583355 0.743059496 0.476707271
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.02296559 -0.01021886 0.67093440
#> grade_iii, Cure model
#> 1.29035968
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 157 15.10 1 47 0 0
#> 8 18.43 1 32 0 0
#> 130 16.47 1 53 0 1
#> 69 23.23 1 25 0 1
#> 145 10.07 1 65 1 0
#> 49 12.19 1 48 1 0
#> 125 15.65 1 67 1 0
#> 149 8.37 1 33 1 0
#> 60 13.15 1 38 1 0
#> 154 12.63 1 20 1 0
#> 96 14.54 1 33 0 1
#> 41 18.02 1 40 1 0
#> 90 20.94 1 50 0 1
#> 25 6.32 1 34 1 0
#> 153 21.33 1 55 1 0
#> 77 7.27 1 67 0 1
#> 24 23.89 1 38 0 0
#> 96.1 14.54 1 33 0 1
#> 181 16.46 1 45 0 1
#> 85 16.44 1 36 0 0
#> 14 12.89 1 21 0 0
#> 199 19.81 1 NA 0 1
#> 106 16.67 1 49 1 0
#> 89 11.44 1 NA 0 0
#> 32 20.90 1 37 1 0
#> 107 11.18 1 54 1 0
#> 180 14.82 1 37 0 0
#> 133 14.65 1 57 0 0
#> 139 21.49 1 63 1 0
#> 134 17.81 1 47 1 0
#> 199.1 19.81 1 NA 0 1
#> 179 18.63 1 42 0 0
#> 124 9.73 1 NA 1 0
#> 169 22.41 1 46 0 0
#> 32.1 20.90 1 37 1 0
#> 124.1 9.73 1 NA 1 0
#> 93 10.33 1 52 0 1
#> 153.1 21.33 1 55 1 0
#> 136 21.83 1 43 0 1
#> 96.2 14.54 1 33 0 1
#> 41.1 18.02 1 40 1 0
#> 25.1 6.32 1 34 1 0
#> 60.1 13.15 1 38 1 0
#> 23 16.92 1 61 0 0
#> 158 20.14 1 74 1 0
#> 86 23.81 1 58 0 1
#> 76 19.22 1 54 0 1
#> 6 15.64 1 39 0 0
#> 96.3 14.54 1 33 0 1
#> 111 17.45 1 47 0 1
#> 127 3.53 1 62 0 1
#> 107.1 11.18 1 54 1 0
#> 52 10.42 1 52 0 1
#> 39 15.59 1 37 0 1
#> 26 15.77 1 49 0 1
#> 5 16.43 1 51 0 1
#> 66 22.13 1 53 0 0
#> 124.2 9.73 1 NA 1 0
#> 169.1 22.41 1 46 0 0
#> 169.2 22.41 1 46 0 0
#> 45 17.42 1 54 0 1
#> 40 18.00 1 28 1 0
#> 100 16.07 1 60 0 0
#> 167 15.55 1 56 1 0
#> 190 20.81 1 42 1 0
#> 123 13.00 1 44 1 0
#> 15 22.68 1 48 0 0
#> 124.3 9.73 1 NA 1 0
#> 61 10.12 1 36 0 1
#> 158.1 20.14 1 74 1 0
#> 128 20.35 1 35 0 1
#> 92 22.92 1 47 0 1
#> 187 9.92 1 39 1 0
#> 91 5.33 1 61 0 1
#> 81 14.06 1 34 0 0
#> 89.1 11.44 1 NA 0 0
#> 181.1 16.46 1 45 0 1
#> 4 17.64 1 NA 0 1
#> 90.1 20.94 1 50 0 1
#> 58 19.34 1 39 0 0
#> 199.2 19.81 1 NA 0 1
#> 6.1 15.64 1 39 0 0
#> 14.1 12.89 1 21 0 0
#> 78 23.88 1 43 0 0
#> 171 16.57 1 41 0 1
#> 24.1 23.89 1 38 0 0
#> 158.2 20.14 1 74 1 0
#> 167.1 15.55 1 56 1 0
#> 97 19.14 1 65 0 1
#> 15.1 22.68 1 48 0 0
#> 105 19.75 1 60 0 0
#> 114 13.68 1 NA 0 0
#> 125.1 15.65 1 67 1 0
#> 81.1 14.06 1 34 0 0
#> 30 17.43 1 78 0 0
#> 197 21.60 1 69 1 0
#> 86.1 23.81 1 58 0 1
#> 181.2 16.46 1 45 0 1
#> 92.1 22.92 1 47 0 1
#> 63 22.77 1 31 1 0
#> 145.1 10.07 1 65 1 0
#> 128.1 20.35 1 35 0 1
#> 159 10.55 1 50 0 1
#> 37 12.52 1 57 1 0
#> 117 17.46 1 26 0 1
#> 159.1 10.55 1 50 0 1
#> 155 13.08 1 26 0 0
#> 78.1 23.88 1 43 0 0
#> 59 10.16 1 NA 1 0
#> 59.1 10.16 1 NA 1 0
#> 39.1 15.59 1 37 0 1
#> 171.1 16.57 1 41 0 1
#> 163 24.00 0 66 0 0
#> 132 24.00 0 55 0 0
#> 198 24.00 0 66 0 1
#> 112 24.00 0 61 0 0
#> 20 24.00 0 46 1 0
#> 200 24.00 0 64 0 0
#> 103 24.00 0 56 1 0
#> 34 24.00 0 36 0 0
#> 64 24.00 0 43 0 0
#> 31 24.00 0 36 0 1
#> 120 24.00 0 68 0 1
#> 112.1 24.00 0 61 0 0
#> 46 24.00 0 71 0 0
#> 44 24.00 0 56 0 0
#> 121 24.00 0 57 1 0
#> 142 24.00 0 53 0 0
#> 178 24.00 0 52 1 0
#> 12 24.00 0 63 0 0
#> 112.2 24.00 0 61 0 0
#> 12.1 24.00 0 63 0 0
#> 47 24.00 0 38 0 1
#> 182 24.00 0 35 0 0
#> 112.3 24.00 0 61 0 0
#> 138 24.00 0 44 1 0
#> 198.1 24.00 0 66 0 1
#> 156 24.00 0 50 1 0
#> 87 24.00 0 27 0 0
#> 1 24.00 0 23 1 0
#> 147 24.00 0 76 1 0
#> 62 24.00 0 71 0 0
#> 156.1 24.00 0 50 1 0
#> 19 24.00 0 57 0 1
#> 178.1 24.00 0 52 1 0
#> 82 24.00 0 34 0 0
#> 109 24.00 0 48 0 0
#> 21 24.00 0 47 0 0
#> 35 24.00 0 51 0 0
#> 31.1 24.00 0 36 0 1
#> 65 24.00 0 57 1 0
#> 200.1 24.00 0 64 0 0
#> 182.1 24.00 0 35 0 0
#> 62.1 24.00 0 71 0 0
#> 12.2 24.00 0 63 0 0
#> 135 24.00 0 58 1 0
#> 28 24.00 0 67 1 0
#> 47.1 24.00 0 38 0 1
#> 160 24.00 0 31 1 0
#> 144 24.00 0 28 0 1
#> 172 24.00 0 41 0 0
#> 47.2 24.00 0 38 0 1
#> 7 24.00 0 37 1 0
#> 34.1 24.00 0 36 0 0
#> 120.1 24.00 0 68 0 1
#> 34.2 24.00 0 36 0 0
#> 48 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 142.1 24.00 0 53 0 0
#> 34.3 24.00 0 36 0 0
#> 3 24.00 0 31 1 0
#> 12.3 24.00 0 63 0 0
#> 152 24.00 0 36 0 1
#> 47.3 24.00 0 38 0 1
#> 64.1 24.00 0 43 0 0
#> 147.1 24.00 0 76 1 0
#> 27 24.00 0 63 1 0
#> 146 24.00 0 63 1 0
#> 67 24.00 0 25 0 0
#> 172.1 24.00 0 41 0 0
#> 94 24.00 0 51 0 1
#> 34.4 24.00 0 36 0 0
#> 80 24.00 0 41 0 0
#> 46.1 24.00 0 71 0 0
#> 162 24.00 0 51 0 0
#> 98 24.00 0 34 1 0
#> 3.1 24.00 0 31 1 0
#> 48.1 24.00 0 31 1 0
#> 19.1 24.00 0 57 0 1
#> 196 24.00 0 19 0 0
#> 161 24.00 0 45 0 0
#> 80.1 24.00 0 41 0 0
#> 144.1 24.00 0 28 0 1
#> 20.1 24.00 0 46 1 0
#> 196.1 24.00 0 19 0 0
#> 174 24.00 0 49 1 0
#> 3.2 24.00 0 31 1 0
#> 103.1 24.00 0 56 1 0
#> 185 24.00 0 44 1 0
#> 71 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.0230 NA NA NA
#> 2 age, Cure model -0.0102 NA NA NA
#> 3 grade_ii, Cure model 0.671 NA NA NA
#> 4 grade_iii, Cure model 1.29 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00558 NA NA NA
#> 2 grade_ii, Survival model 0.743 NA NA NA
#> 3 grade_iii, Survival model 0.477 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.02297 -0.01022 0.67093 1.29036
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258.6
#> Residual Deviance: 245.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.02296559 -0.01021886 0.67093440 1.29035968
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.005583355 0.743059496 0.476707271
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.708084156 0.435627924 0.561424770 0.091234244 0.926088246 0.858271131
#> [7] 0.635486771 0.951034167 0.788214815 0.840885296 0.735270647 0.445918156
#> [13] 0.278881951 0.967530766 0.255686116 0.959286298 0.009855457 0.735270647
#> [19] 0.570836206 0.598270361 0.823383885 0.533159073 0.301665230 0.866887585
#> [25] 0.717121810 0.726180773 0.243178621 0.475452069 0.425377317 0.166951978
#> [31] 0.301665230 0.909207641 0.255686116 0.217218020 0.735270647 0.445918156
#> [37] 0.967530766 0.788214815 0.523516798 0.354788660 0.063509274 0.404948605
#> [43] 0.653701285 0.735270647 0.494738603 0.991877717 0.866887585 0.900738888
#> [49] 0.672015679 0.626193595 0.607584867 0.203865278 0.166951978 0.166951978
#> [55] 0.513925516 0.465647949 0.616869255 0.690176619 0.323290233 0.814606937
#> [61] 0.142622557 0.917660266 0.354788660 0.334047299 0.105414084 0.942728084
#> [67] 0.983746149 0.770382871 0.570836206 0.278881951 0.394669406 0.653701285
#> [73] 0.823383885 0.033932737 0.542697994 0.009855457 0.354788660 0.690176619
#> [79] 0.415178097 0.142622557 0.384442340 0.635486771 0.770382871 0.504299842
#> [85] 0.230355486 0.063509274 0.570836206 0.105414084 0.130407218 0.926088246
#> [91] 0.334047299 0.883848625 0.849601752 0.485133007 0.883848625 0.805768623
#> [97] 0.033932737 0.672015679 0.542697994 0.000000000 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 157 8 130 69 145 49 125 149 60 154 96 41 90
#> 15.10 18.43 16.47 23.23 10.07 12.19 15.65 8.37 13.15 12.63 14.54 18.02 20.94
#> 25 153 77 24 96.1 181 85 14 106 32 107 180 133
#> 6.32 21.33 7.27 23.89 14.54 16.46 16.44 12.89 16.67 20.90 11.18 14.82 14.65
#> 139 134 179 169 32.1 93 153.1 136 96.2 41.1 25.1 60.1 23
#> 21.49 17.81 18.63 22.41 20.90 10.33 21.33 21.83 14.54 18.02 6.32 13.15 16.92
#> 158 86 76 6 96.3 111 127 107.1 52 39 26 5 66
#> 20.14 23.81 19.22 15.64 14.54 17.45 3.53 11.18 10.42 15.59 15.77 16.43 22.13
#> 169.1 169.2 45 40 100 167 190 123 15 61 158.1 128 92
#> 22.41 22.41 17.42 18.00 16.07 15.55 20.81 13.00 22.68 10.12 20.14 20.35 22.92
#> 187 91 81 181.1 90.1 58 6.1 14.1 78 171 24.1 158.2 167.1
#> 9.92 5.33 14.06 16.46 20.94 19.34 15.64 12.89 23.88 16.57 23.89 20.14 15.55
#> 97 15.1 105 125.1 81.1 30 197 86.1 181.2 92.1 63 145.1 128.1
#> 19.14 22.68 19.75 15.65 14.06 17.43 21.60 23.81 16.46 22.92 22.77 10.07 20.35
#> 159 37 117 159.1 155 78.1 39.1 171.1 163 132 198 112 20
#> 10.55 12.52 17.46 10.55 13.08 23.88 15.59 16.57 24.00 24.00 24.00 24.00 24.00
#> 200 103 34 64 31 120 112.1 46 44 121 142 178 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112.2 12.1 47 182 112.3 138 198.1 156 87 1 147 62 156.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 178.1 82 109 21 35 31.1 65 200.1 182.1 62.1 12.2 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 47.1 160 144 172 47.2 7 34.1 120.1 34.2 48 151 142.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34.3 3 12.3 152 47.3 64.1 147.1 27 146 67 172.1 94 34.4
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 46.1 162 98 3.1 48.1 19.1 196 161 80.1 144.1 20.1 196.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 3.2 103.1 185 71
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[10]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00909549 0.50647365 0.04949100
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.092450504 -0.002695911 0.428516858
#> grade_iii, Cure model
#> 0.764428577
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 4 17.64 1 NA 0 1
#> 110 17.56 1 65 0 1
#> 101 9.97 1 10 0 1
#> 136 21.83 1 43 0 1
#> 15 22.68 1 48 0 0
#> 134 17.81 1 47 1 0
#> 183 9.24 1 67 1 0
#> 194 22.40 1 38 0 1
#> 199 19.81 1 NA 0 1
#> 183.1 9.24 1 67 1 0
#> 183.2 9.24 1 67 1 0
#> 175 21.91 1 43 0 0
#> 29 15.45 1 68 1 0
#> 123 13.00 1 44 1 0
#> 81 14.06 1 34 0 0
#> 93 10.33 1 52 0 1
#> 192 16.44 1 31 1 0
#> 69 23.23 1 25 0 1
#> 124 9.73 1 NA 1 0
#> 88 18.37 1 47 0 0
#> 169 22.41 1 46 0 0
#> 190 20.81 1 42 1 0
#> 55 19.34 1 69 0 1
#> 128 20.35 1 35 0 1
#> 187 9.92 1 39 1 0
#> 49 12.19 1 48 1 0
#> 29.1 15.45 1 68 1 0
#> 41 18.02 1 40 1 0
#> 40 18.00 1 28 1 0
#> 96 14.54 1 33 0 1
#> 39 15.59 1 37 0 1
#> 184 17.77 1 38 0 0
#> 49.1 12.19 1 48 1 0
#> 10 10.53 1 34 0 0
#> 111 17.45 1 47 0 1
#> 56 12.21 1 60 0 0
#> 97 19.14 1 65 0 1
#> 85 16.44 1 36 0 0
#> 29.2 15.45 1 68 1 0
#> 88.1 18.37 1 47 0 0
#> 164 23.60 1 76 0 1
#> 16 8.71 1 71 0 1
#> 41.1 18.02 1 40 1 0
#> 128.1 20.35 1 35 0 1
#> 124.1 9.73 1 NA 1 0
#> 108 18.29 1 39 0 1
#> 153 21.33 1 55 1 0
#> 45 17.42 1 54 0 1
#> 175.1 21.91 1 43 0 0
#> 51 18.23 1 83 0 1
#> 150 20.33 1 48 0 0
#> 56.1 12.21 1 60 0 0
#> 50 10.02 1 NA 1 0
#> 111.1 17.45 1 47 0 1
#> 190.1 20.81 1 42 1 0
#> 89 11.44 1 NA 0 0
#> 40.1 18.00 1 28 1 0
#> 101.1 9.97 1 10 0 1
#> 66 22.13 1 53 0 0
#> 81.1 14.06 1 34 0 0
#> 180 14.82 1 37 0 0
#> 85.1 16.44 1 36 0 0
#> 169.1 22.41 1 46 0 0
#> 41.2 18.02 1 40 1 0
#> 50.1 10.02 1 NA 1 0
#> 158 20.14 1 74 1 0
#> 61 10.12 1 36 0 1
#> 86 23.81 1 58 0 1
#> 183.3 9.24 1 67 1 0
#> 114 13.68 1 NA 0 0
#> 150.1 20.33 1 48 0 0
#> 81.2 14.06 1 34 0 0
#> 52 10.42 1 52 0 1
#> 139 21.49 1 63 1 0
#> 79 16.23 1 54 1 0
#> 129 23.41 1 53 1 0
#> 166 19.98 1 48 0 0
#> 24 23.89 1 38 0 0
#> 181 16.46 1 45 0 1
#> 90 20.94 1 50 0 1
#> 181.1 16.46 1 45 0 1
#> 93.1 10.33 1 52 0 1
#> 187.1 9.92 1 39 1 0
#> 30 17.43 1 78 0 0
#> 101.2 9.97 1 10 0 1
#> 10.1 10.53 1 34 0 0
#> 105 19.75 1 60 0 0
#> 56.2 12.21 1 60 0 0
#> 171 16.57 1 41 0 1
#> 14 12.89 1 21 0 0
#> 149 8.37 1 33 1 0
#> 171.1 16.57 1 41 0 1
#> 25 6.32 1 34 1 0
#> 99 21.19 1 38 0 1
#> 194.1 22.40 1 38 0 1
#> 18 15.21 1 49 1 0
#> 184.1 17.77 1 38 0 0
#> 41.3 18.02 1 40 1 0
#> 32 20.90 1 37 1 0
#> 123.1 13.00 1 44 1 0
#> 32.1 20.90 1 37 1 0
#> 154 12.63 1 20 1 0
#> 99.1 21.19 1 38 0 1
#> 76 19.22 1 54 0 1
#> 51.1 18.23 1 83 0 1
#> 29.3 15.45 1 68 1 0
#> 60 13.15 1 38 1 0
#> 192.1 16.44 1 31 1 0
#> 86.1 23.81 1 58 0 1
#> 100 16.07 1 60 0 0
#> 52.1 10.42 1 52 0 1
#> 101.3 9.97 1 10 0 1
#> 147 24.00 0 76 1 0
#> 147.1 24.00 0 76 1 0
#> 19 24.00 0 57 0 1
#> 193 24.00 0 45 0 1
#> 191 24.00 0 60 0 1
#> 200 24.00 0 64 0 0
#> 74 24.00 0 43 0 1
#> 163 24.00 0 66 0 0
#> 143 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 22 24.00 0 52 1 0
#> 71 24.00 0 51 0 0
#> 11 24.00 0 42 0 1
#> 84 24.00 0 39 0 1
#> 11.1 24.00 0 42 0 1
#> 27 24.00 0 63 1 0
#> 17 24.00 0 38 0 1
#> 11.2 24.00 0 42 0 1
#> 22.1 24.00 0 52 1 0
#> 143.1 24.00 0 51 0 0
#> 120 24.00 0 68 0 1
#> 64 24.00 0 43 0 0
#> 198 24.00 0 66 0 1
#> 9 24.00 0 31 1 0
#> 54 24.00 0 53 1 0
#> 20 24.00 0 46 1 0
#> 19.1 24.00 0 57 0 1
#> 196 24.00 0 19 0 0
#> 75 24.00 0 21 1 0
#> 165 24.00 0 47 0 0
#> 196.1 24.00 0 19 0 0
#> 20.1 24.00 0 46 1 0
#> 172 24.00 0 41 0 0
#> 191.1 24.00 0 60 0 1
#> 67 24.00 0 25 0 0
#> 144 24.00 0 28 0 1
#> 185 24.00 0 44 1 0
#> 160 24.00 0 31 1 0
#> 135 24.00 0 58 1 0
#> 1 24.00 0 23 1 0
#> 182 24.00 0 35 0 0
#> 22.2 24.00 0 52 1 0
#> 163.1 24.00 0 66 0 0
#> 67.1 24.00 0 25 0 0
#> 144.1 24.00 0 28 0 1
#> 62 24.00 0 71 0 0
#> 22.3 24.00 0 52 1 0
#> 200.1 24.00 0 64 0 0
#> 165.1 24.00 0 47 0 0
#> 162 24.00 0 51 0 0
#> 38 24.00 0 31 1 0
#> 82 24.00 0 34 0 0
#> 146 24.00 0 63 1 0
#> 112 24.00 0 61 0 0
#> 103 24.00 0 56 1 0
#> 44 24.00 0 56 0 0
#> 126 24.00 0 48 0 0
#> 160.1 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 64.1 24.00 0 43 0 0
#> 9.1 24.00 0 31 1 0
#> 186 24.00 0 45 1 0
#> 193.1 24.00 0 45 0 1
#> 147.2 24.00 0 76 1 0
#> 163.2 24.00 0 66 0 0
#> 67.2 24.00 0 25 0 0
#> 9.2 24.00 0 31 1 0
#> 38.1 24.00 0 31 1 0
#> 198.1 24.00 0 66 0 1
#> 47 24.00 0 38 0 1
#> 156 24.00 0 50 1 0
#> 82.1 24.00 0 34 0 0
#> 71.1 24.00 0 51 0 0
#> 3 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 3.1 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 46 24.00 0 71 0 0
#> 72 24.00 0 40 0 1
#> 54.1 24.00 0 53 1 0
#> 122 24.00 0 66 0 0
#> 11.3 24.00 0 42 0 1
#> 191.2 24.00 0 60 0 1
#> 193.2 24.00 0 45 0 1
#> 138 24.00 0 44 1 0
#> 34 24.00 0 36 0 0
#> 44.1 24.00 0 56 0 0
#> 21.1 24.00 0 47 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.0925 NA NA NA
#> 2 age, Cure model -0.00270 NA NA NA
#> 3 grade_ii, Cure model 0.429 NA NA NA
#> 4 grade_iii, Cure model 0.764 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00910 NA NA NA
#> 2 grade_ii, Survival model 0.506 NA NA NA
#> 3 grade_iii, Survival model 0.0495 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.092451 -0.002696 0.428517 0.764429
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.8
#> Residual Deviance: 260.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.092450504 -0.002695911 0.428516858 0.764428577
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00909549 0.50647365 0.04949100
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.3881080536 0.8519904211 0.0811782465 0.0270447654 0.3587249616
#> [6] 0.9200446976 0.0454111258 0.9200446976 0.9200446976 0.0661312409
#> [11] 0.5545806966 0.6734848656 0.6296489427 0.8176741195 0.4809726647
#> [16] 0.0214743456 0.2519468223 0.0330562882 0.1471125883 0.2237380221
#> [21] 0.1632651721 0.8972285413 0.7505363356 0.5545806966 0.3012099168
#> [26] 0.3393872860 0.6186876182 0.5437726089 0.3685057891 0.7505363356
#> [31] 0.7727285798 0.3981435505 0.7174250026 0.2423961832 0.4809726647
#> [36] 0.5545806966 0.2519468223 0.0107710934 0.9653285396 0.3012099168
#> [41] 0.1632651721 0.2711842258 0.0975040920 0.4285958961 0.0661312409
#> [46] 0.2810738419 0.1798045535 0.7174250026 0.3981435505 0.1471125883
#> [51] 0.3393872860 0.8519904211 0.0587116916 0.6296489427 0.6077691864
#> [56] 0.4809726647 0.0330562882 0.3012099168 0.1969010071 0.8404739560
#> [61] 0.0038576027 0.9200446976 0.1798045535 0.6296489427 0.7950916964
#> [66] 0.0893169124 0.5223536222 0.0161359492 0.2057033389 0.0009391014
#> [71] 0.4598436348 0.1220481154 0.4598436348 0.8176741195 0.8972285413
#> [76] 0.4182771882 0.8519904211 0.7727285798 0.2146410062 0.7174250026
#> [81] 0.4390040790 0.6953699461 0.9769164262 0.4390040790 0.9884729030
#> [86] 0.1056873904 0.0454111258 0.5969065226 0.3685057891 0.3012099168
#> [91] 0.1307235908 0.6734848656 0.1307235908 0.7064304736 0.1056873904
#> [96] 0.2330004090 0.2810738419 0.5545806966 0.6624113087 0.4809726647
#> [101] 0.0038576027 0.5330178646 0.7950916964 0.8519904211 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [191] 0.0000000000 0.0000000000
#>
#> $Time
#> 110 101 136 15 134 183 194 183.1 183.2 175 29 123 81
#> 17.56 9.97 21.83 22.68 17.81 9.24 22.40 9.24 9.24 21.91 15.45 13.00 14.06
#> 93 192 69 88 169 190 55 128 187 49 29.1 41 40
#> 10.33 16.44 23.23 18.37 22.41 20.81 19.34 20.35 9.92 12.19 15.45 18.02 18.00
#> 96 39 184 49.1 10 111 56 97 85 29.2 88.1 164 16
#> 14.54 15.59 17.77 12.19 10.53 17.45 12.21 19.14 16.44 15.45 18.37 23.60 8.71
#> 41.1 128.1 108 153 45 175.1 51 150 56.1 111.1 190.1 40.1 101.1
#> 18.02 20.35 18.29 21.33 17.42 21.91 18.23 20.33 12.21 17.45 20.81 18.00 9.97
#> 66 81.1 180 85.1 169.1 41.2 158 61 86 183.3 150.1 81.2 52
#> 22.13 14.06 14.82 16.44 22.41 18.02 20.14 10.12 23.81 9.24 20.33 14.06 10.42
#> 139 79 129 166 24 181 90 181.1 93.1 187.1 30 101.2 10.1
#> 21.49 16.23 23.41 19.98 23.89 16.46 20.94 16.46 10.33 9.92 17.43 9.97 10.53
#> 105 56.2 171 14 149 171.1 25 99 194.1 18 184.1 41.3 32
#> 19.75 12.21 16.57 12.89 8.37 16.57 6.32 21.19 22.40 15.21 17.77 18.02 20.90
#> 123.1 32.1 154 99.1 76 51.1 29.3 60 192.1 86.1 100 52.1 101.3
#> 13.00 20.90 12.63 21.19 19.22 18.23 15.45 13.15 16.44 23.81 16.07 10.42 9.97
#> 147 147.1 19 193 191 200 74 163 143 21 22 71 11
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 11.1 27 17 11.2 22.1 143.1 120 64 198 9 54 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19.1 196 75 165 196.1 20.1 172 191.1 67 144 185 160 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 182 22.2 163.1 67.1 144.1 62 22.3 200.1 165.1 162 38 82
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 112 103 44 126 160.1 80 64.1 9.1 186 193.1 147.2 163.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67.2 9.2 38.1 198.1 47 156 82.1 71.1 3 119 3.1 151 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72 54.1 122 11.3 191.2 193.2 138 34 44.1 21.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[11]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.006850478 0.823449188 0.283255163
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.070415490 -0.005650346 0.436014050
#> grade_iii, Cure model
#> 1.287220203
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 88 18.37 1 47 0 0
#> 155 13.08 1 26 0 0
#> 166 19.98 1 48 0 0
#> 159 10.55 1 50 0 1
#> 91 5.33 1 61 0 1
#> 106 16.67 1 49 1 0
#> 61 10.12 1 36 0 1
#> 51 18.23 1 83 0 1
#> 113 22.86 1 34 0 0
#> 140 12.68 1 59 1 0
#> 77 7.27 1 67 0 1
#> 125 15.65 1 67 1 0
#> 50 10.02 1 NA 1 0
#> 36 21.19 1 48 0 1
#> 166.1 19.98 1 48 0 0
#> 57 14.46 1 45 0 1
#> 50.1 10.02 1 NA 1 0
#> 195 11.76 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 195.1 11.76 1 NA 1 0
#> 6 15.64 1 39 0 0
#> 60 13.15 1 38 1 0
#> 6.1 15.64 1 39 0 0
#> 79 16.23 1 54 1 0
#> 85 16.44 1 36 0 0
#> 66 22.13 1 53 0 0
#> 49 12.19 1 48 1 0
#> 175 21.91 1 43 0 0
#> 30 17.43 1 78 0 0
#> 52 10.42 1 52 0 1
#> 192 16.44 1 31 1 0
#> 187 9.92 1 39 1 0
#> 70 7.38 1 30 1 0
#> 92 22.92 1 47 0 1
#> 106.1 16.67 1 49 1 0
#> 92.1 22.92 1 47 0 1
#> 127 3.53 1 62 0 1
#> 78 23.88 1 43 0 0
#> 114 13.68 1 NA 0 0
#> 59 10.16 1 NA 1 0
#> 93 10.33 1 52 0 1
#> 150 20.33 1 48 0 0
#> 5 16.43 1 51 0 1
#> 181 16.46 1 45 0 1
#> 194 22.40 1 38 0 1
#> 81 14.06 1 34 0 0
#> 195.2 11.76 1 NA 1 0
#> 190 20.81 1 42 1 0
#> 164 23.60 1 76 0 1
#> 125.1 15.65 1 67 1 0
#> 76 19.22 1 54 0 1
#> 88.1 18.37 1 47 0 0
#> 61.1 10.12 1 36 0 1
#> 99 21.19 1 38 0 1
#> 199 19.81 1 NA 0 1
#> 149 8.37 1 33 1 0
#> 166.2 19.98 1 48 0 0
#> 36.1 21.19 1 48 0 1
#> 194.1 22.40 1 38 0 1
#> 180 14.82 1 37 0 0
#> 23 16.92 1 61 0 0
#> 23.1 16.92 1 61 0 0
#> 169 22.41 1 46 0 0
#> 190.1 20.81 1 42 1 0
#> 56 12.21 1 60 0 0
#> 194.2 22.40 1 38 0 1
#> 134 17.81 1 47 1 0
#> 96 14.54 1 33 0 1
#> 79.1 16.23 1 54 1 0
#> 187.1 9.92 1 39 1 0
#> 110 17.56 1 65 0 1
#> 61.2 10.12 1 36 0 1
#> 110.1 17.56 1 65 0 1
#> 25 6.32 1 34 1 0
#> 194.3 22.40 1 38 0 1
#> 105 19.75 1 60 0 0
#> 194.4 22.40 1 38 0 1
#> 99.1 21.19 1 38 0 1
#> 123 13.00 1 44 1 0
#> 41 18.02 1 40 1 0
#> 179 18.63 1 42 0 0
#> 16 8.71 1 71 0 1
#> 78.1 23.88 1 43 0 0
#> 85.1 16.44 1 36 0 0
#> 166.3 19.98 1 48 0 0
#> 24 23.89 1 38 0 0
#> 85.2 16.44 1 36 0 0
#> 49.1 12.19 1 48 1 0
#> 4 17.64 1 NA 0 1
#> 32 20.90 1 37 1 0
#> 153 21.33 1 55 1 0
#> 187.2 9.92 1 39 1 0
#> 136 21.83 1 43 0 1
#> 127.1 3.53 1 62 0 1
#> 181.1 16.46 1 45 0 1
#> 25.1 6.32 1 34 1 0
#> 130 16.47 1 53 0 1
#> 85.3 16.44 1 36 0 0
#> 123.1 13.00 1 44 1 0
#> 111 17.45 1 47 0 1
#> 8.1 18.43 1 32 0 0
#> 76.1 19.22 1 54 0 1
#> 57.1 14.46 1 45 0 1
#> 45 17.42 1 54 0 1
#> 50.2 10.02 1 NA 1 0
#> 61.3 10.12 1 36 0 1
#> 63 22.77 1 31 1 0
#> 106.2 16.67 1 49 1 0
#> 29 15.45 1 68 1 0
#> 39 15.59 1 37 0 1
#> 96.1 14.54 1 33 0 1
#> 134.1 17.81 1 47 1 0
#> 121 24.00 0 57 1 0
#> 21 24.00 0 47 0 0
#> 12 24.00 0 63 0 0
#> 34 24.00 0 36 0 0
#> 165 24.00 0 47 0 0
#> 12.1 24.00 0 63 0 0
#> 146 24.00 0 63 1 0
#> 44 24.00 0 56 0 0
#> 116 24.00 0 58 0 1
#> 38 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 21.1 24.00 0 47 0 0
#> 64 24.00 0 43 0 0
#> 73 24.00 0 NA 0 1
#> 94 24.00 0 51 0 1
#> 64.1 24.00 0 43 0 0
#> 62 24.00 0 71 0 0
#> 132 24.00 0 55 0 0
#> 147 24.00 0 76 1 0
#> 62.1 24.00 0 71 0 0
#> 176 24.00 0 43 0 1
#> 143 24.00 0 51 0 0
#> 72 24.00 0 40 0 1
#> 80 24.00 0 41 0 0
#> 193 24.00 0 45 0 1
#> 161 24.00 0 45 0 0
#> 1 24.00 0 23 1 0
#> 116.1 24.00 0 58 0 1
#> 83 24.00 0 6 0 0
#> 135 24.00 0 58 1 0
#> 2 24.00 0 9 0 0
#> 112 24.00 0 61 0 0
#> 83.1 24.00 0 6 0 0
#> 122 24.00 0 66 0 0
#> 165.1 24.00 0 47 0 0
#> 182 24.00 0 35 0 0
#> 141 24.00 0 44 1 0
#> 109 24.00 0 48 0 0
#> 176.1 24.00 0 43 0 1
#> 82 24.00 0 34 0 0
#> 193.1 24.00 0 45 0 1
#> 182.1 24.00 0 35 0 0
#> 53 24.00 0 32 0 1
#> 185 24.00 0 44 1 0
#> 75 24.00 0 21 1 0
#> 62.2 24.00 0 71 0 0
#> 72.1 24.00 0 40 0 1
#> 116.2 24.00 0 58 0 1
#> 163 24.00 0 66 0 0
#> 71 24.00 0 51 0 0
#> 64.2 24.00 0 43 0 0
#> 2.1 24.00 0 9 0 0
#> 196 24.00 0 19 0 0
#> 163.1 24.00 0 66 0 0
#> 12.2 24.00 0 63 0 0
#> 38.1 24.00 0 31 1 0
#> 146.1 24.00 0 63 1 0
#> 135.1 24.00 0 58 1 0
#> 126 24.00 0 48 0 0
#> 54 24.00 0 53 1 0
#> 103 24.00 0 56 1 0
#> 109.1 24.00 0 48 0 0
#> 126.1 24.00 0 48 0 0
#> 198 24.00 0 66 0 1
#> 160 24.00 0 31 1 0
#> 115 24.00 0 NA 1 0
#> 31 24.00 0 36 0 1
#> 65 24.00 0 57 1 0
#> 64.3 24.00 0 43 0 0
#> 1.1 24.00 0 23 1 0
#> 11 24.00 0 42 0 1
#> 7 24.00 0 37 1 0
#> 156 24.00 0 50 1 0
#> 193.2 24.00 0 45 0 1
#> 138 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 109.2 24.00 0 48 0 0
#> 135.2 24.00 0 58 1 0
#> 137 24.00 0 45 1 0
#> 62.3 24.00 0 71 0 0
#> 83.2 24.00 0 6 0 0
#> 186 24.00 0 45 1 0
#> 185.1 24.00 0 44 1 0
#> 65.1 24.00 0 57 1 0
#> 198.1 24.00 0 66 0 1
#> 131 24.00 0 66 0 0
#> 165.2 24.00 0 47 0 0
#> 142 24.00 0 53 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.0704 NA NA NA
#> 2 age, Cure model -0.00565 NA NA NA
#> 3 grade_ii, Cure model 0.436 NA NA NA
#> 4 grade_iii, Cure model 1.29 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00685 NA NA NA
#> 2 grade_ii, Survival model 0.823 NA NA NA
#> 3 grade_iii, Survival model 0.283 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.07042 -0.00565 0.43601 1.28722
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.3
#> Residual Deviance: 246.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.070415490 -0.005650346 0.436014050 1.287220203
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.006850478 0.823449188 0.283255163
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.58953384 0.86671116 0.49677825 0.90525071 0.98585541 0.69505780
#> [7] 0.92112371 0.60743784 0.23063721 0.88359720 0.97145892 0.78926959
#> [13] 0.41143107 0.49677825 0.84350157 0.57142095 0.80152237 0.86096110
#> [19] 0.80152237 0.77650036 0.73684069 0.35649077 0.89459060 0.37081810
#> [25] 0.66453423 0.91056923 0.73684069 0.94167306 0.96656578 0.18837163
#> [31] 0.69505780 0.18837163 0.99060874 0.09706242 0.91586009 0.48681468
#> [37] 0.76983639 0.72309442 0.28929886 0.85513493 0.46693470 0.16038204
#> [43] 0.78926959 0.54386803 0.58953384 0.92112371 0.41143107 0.96162768
#> [49] 0.49677825 0.41143107 0.28929886 0.82577806 0.67996802 0.67996802
#> [55] 0.27102990 0.46693470 0.88910253 0.28929886 0.62487660 0.83173732
#> [61] 0.77650036 0.94167306 0.64100613 0.92112371 0.64100613 0.97632509
#> [67] 0.28929886 0.53431390 0.28929886 0.41143107 0.87245380 0.61628035
#> [73] 0.56221955 0.95664206 0.09706242 0.73684069 0.49677825 0.04490495
#> [79] 0.73684069 0.89459060 0.45592068 0.39870382 0.94167306 0.38495837
#> [85] 0.99060874 0.72309442 0.97632509 0.71608021 0.73684069 0.87245380
#> [91] 0.65671202 0.57142095 0.54386803 0.84350157 0.67229194 0.92112371
#> [97] 0.25229379 0.69505780 0.81980638 0.81371805 0.83173732 0.62487660
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 88 155 166 159 91 106 61 51 113 140 77 125 36
#> 18.37 13.08 19.98 10.55 5.33 16.67 10.12 18.23 22.86 12.68 7.27 15.65 21.19
#> 166.1 57 8 6 60 6.1 79 85 66 49 175 30 52
#> 19.98 14.46 18.43 15.64 13.15 15.64 16.23 16.44 22.13 12.19 21.91 17.43 10.42
#> 192 187 70 92 106.1 92.1 127 78 93 150 5 181 194
#> 16.44 9.92 7.38 22.92 16.67 22.92 3.53 23.88 10.33 20.33 16.43 16.46 22.40
#> 81 190 164 125.1 76 88.1 61.1 99 149 166.2 36.1 194.1 180
#> 14.06 20.81 23.60 15.65 19.22 18.37 10.12 21.19 8.37 19.98 21.19 22.40 14.82
#> 23 23.1 169 190.1 56 194.2 134 96 79.1 187.1 110 61.2 110.1
#> 16.92 16.92 22.41 20.81 12.21 22.40 17.81 14.54 16.23 9.92 17.56 10.12 17.56
#> 25 194.3 105 194.4 99.1 123 41 179 16 78.1 85.1 166.3 24
#> 6.32 22.40 19.75 22.40 21.19 13.00 18.02 18.63 8.71 23.88 16.44 19.98 23.89
#> 85.2 49.1 32 153 187.2 136 127.1 181.1 25.1 130 85.3 123.1 111
#> 16.44 12.19 20.90 21.33 9.92 21.83 3.53 16.46 6.32 16.47 16.44 13.00 17.45
#> 8.1 76.1 57.1 45 61.3 63 106.2 29 39 96.1 134.1 121 21
#> 18.43 19.22 14.46 17.42 10.12 22.77 16.67 15.45 15.59 14.54 17.81 24.00 24.00
#> 12 34 165 12.1 146 44 116 38 98 21.1 64 94 64.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 132 147 62.1 176 143 72 80 193 161 1 116.1 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 2 112 83.1 122 165.1 182 141 109 176.1 82 193.1 182.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 185 75 62.2 72.1 116.2 163 71 64.2 2.1 196 163.1 12.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38.1 146.1 135.1 126 54 103 109.1 126.1 198 160 31 65 64.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1.1 11 7 156 193.2 138 27 109.2 135.2 137 62.3 83.2 186
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185.1 65.1 198.1 131 165.2 142
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[12]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0008214519 0.6518281444 0.4875132089
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.57973213 0.02607299 0.51572334
#> grade_iii, Cure model
#> 0.93664016
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 194 22.40 1 38 0 1
#> 175 21.91 1 43 0 0
#> 158 20.14 1 74 1 0
#> 114 13.68 1 NA 0 0
#> 60 13.15 1 38 1 0
#> 14 12.89 1 21 0 0
#> 18 15.21 1 49 1 0
#> 168 23.72 1 70 0 0
#> 129 23.41 1 53 1 0
#> 68 20.62 1 44 0 0
#> 199 19.81 1 NA 0 1
#> 59 10.16 1 NA 1 0
#> 188 16.16 1 46 0 1
#> 51 18.23 1 83 0 1
#> 150 20.33 1 48 0 0
#> 96 14.54 1 33 0 1
#> 50 10.02 1 NA 1 0
#> 150.1 20.33 1 48 0 0
#> 125 15.65 1 67 1 0
#> 37 12.52 1 57 1 0
#> 187 9.92 1 39 1 0
#> 57 14.46 1 45 0 1
#> 114.1 13.68 1 NA 0 0
#> 89 11.44 1 NA 0 0
#> 139 21.49 1 63 1 0
#> 128 20.35 1 35 0 1
#> 108 18.29 1 39 0 1
#> 187.1 9.92 1 39 1 0
#> 63 22.77 1 31 1 0
#> 189 10.51 1 NA 1 0
#> 140 12.68 1 59 1 0
#> 85 16.44 1 36 0 0
#> 192 16.44 1 31 1 0
#> 110 17.56 1 65 0 1
#> 96.1 14.54 1 33 0 1
#> 58 19.34 1 39 0 0
#> 100 16.07 1 60 0 0
#> 187.2 9.92 1 39 1 0
#> 89.1 11.44 1 NA 0 0
#> 32 20.90 1 37 1 0
#> 41 18.02 1 40 1 0
#> 177 12.53 1 75 0 0
#> 30 17.43 1 78 0 0
#> 139.1 21.49 1 63 1 0
#> 192.1 16.44 1 31 1 0
#> 106 16.67 1 49 1 0
#> 158.1 20.14 1 74 1 0
#> 167 15.55 1 56 1 0
#> 16 8.71 1 71 0 1
#> 68.1 20.62 1 44 0 0
#> 157 15.10 1 47 0 0
#> 140.1 12.68 1 59 1 0
#> 145 10.07 1 65 1 0
#> 123 13.00 1 44 1 0
#> 149 8.37 1 33 1 0
#> 128.1 20.35 1 35 0 1
#> 134 17.81 1 47 1 0
#> 114.2 13.68 1 NA 0 0
#> 77 7.27 1 67 0 1
#> 8 18.43 1 32 0 0
#> 195 11.76 1 NA 1 0
#> 149.1 8.37 1 33 1 0
#> 91 5.33 1 61 0 1
#> 24 23.89 1 38 0 0
#> 125.1 15.65 1 67 1 0
#> 123.1 13.00 1 44 1 0
#> 4 17.64 1 NA 0 1
#> 92 22.92 1 47 0 1
#> 26 15.77 1 49 0 1
#> 159 10.55 1 50 0 1
#> 164 23.60 1 76 0 1
#> 130 16.47 1 53 0 1
#> 4.1 17.64 1 NA 0 1
#> 42 12.43 1 49 0 1
#> 57.1 14.46 1 45 0 1
#> 180 14.82 1 37 0 0
#> 93 10.33 1 52 0 1
#> 133 14.65 1 57 0 0
#> 106.1 16.67 1 49 1 0
#> 159.1 10.55 1 50 0 1
#> 26.1 15.77 1 49 0 1
#> 170 19.54 1 43 0 1
#> 16.1 8.71 1 71 0 1
#> 18.1 15.21 1 49 1 0
#> 157.1 15.10 1 47 0 0
#> 55 19.34 1 69 0 1
#> 50.1 10.02 1 NA 1 0
#> 123.2 13.00 1 44 1 0
#> 91.1 5.33 1 61 0 1
#> 167.1 15.55 1 56 1 0
#> 189.1 10.51 1 NA 1 0
#> 92.1 22.92 1 47 0 1
#> 24.1 23.89 1 38 0 0
#> 187.3 9.92 1 39 1 0
#> 194.1 22.40 1 38 0 1
#> 199.1 19.81 1 NA 0 1
#> 36 21.19 1 48 0 1
#> 6 15.64 1 39 0 0
#> 180.1 14.82 1 37 0 0
#> 43 12.10 1 61 0 1
#> 43.1 12.10 1 61 0 1
#> 190 20.81 1 42 1 0
#> 58.1 19.34 1 39 0 0
#> 175.1 21.91 1 43 0 0
#> 79 16.23 1 54 1 0
#> 159.2 10.55 1 50 0 1
#> 61 10.12 1 36 0 1
#> 39 15.59 1 37 0 1
#> 159.3 10.55 1 50 0 1
#> 86 23.81 1 58 0 1
#> 15 22.68 1 48 0 0
#> 108.1 18.29 1 39 0 1
#> 102 24.00 0 49 0 0
#> 17 24.00 0 38 0 1
#> 131 24.00 0 66 0 0
#> 84 24.00 0 39 0 1
#> 137 24.00 0 45 1 0
#> 156 24.00 0 50 1 0
#> 126 24.00 0 48 0 0
#> 84.1 24.00 0 39 0 1
#> 34 24.00 0 36 0 0
#> 131.1 24.00 0 66 0 0
#> 3 24.00 0 31 1 0
#> 196 24.00 0 19 0 0
#> 178 24.00 0 52 1 0
#> 17.1 24.00 0 38 0 1
#> 2 24.00 0 9 0 0
#> 3.1 24.00 0 31 1 0
#> 103 24.00 0 56 1 0
#> 200 24.00 0 64 0 0
#> 193 24.00 0 45 0 1
#> 163 24.00 0 66 0 0
#> 2.1 24.00 0 9 0 0
#> 176 24.00 0 43 0 1
#> 173 24.00 0 19 0 1
#> 162 24.00 0 51 0 0
#> 165 24.00 0 47 0 0
#> 151 24.00 0 42 0 0
#> 112 24.00 0 61 0 0
#> 172 24.00 0 41 0 0
#> 193.1 24.00 0 45 0 1
#> 119 24.00 0 17 0 0
#> 120 24.00 0 68 0 1
#> 144 24.00 0 28 0 1
#> 156.1 24.00 0 50 1 0
#> 147 24.00 0 76 1 0
#> 182 24.00 0 35 0 0
#> 182.1 24.00 0 35 0 0
#> 54 24.00 0 53 1 0
#> 9 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 109 24.00 0 48 0 0
#> 44 24.00 0 56 0 0
#> 94 24.00 0 51 0 1
#> 48 24.00 0 31 1 0
#> 178.1 24.00 0 52 1 0
#> 176.1 24.00 0 43 0 1
#> 121 24.00 0 57 1 0
#> 163.1 24.00 0 66 0 0
#> 174 24.00 0 49 1 0
#> 174.1 24.00 0 49 1 0
#> 182.2 24.00 0 35 0 0
#> 119.1 24.00 0 17 0 0
#> 103.1 24.00 0 56 1 0
#> 98 24.00 0 34 1 0
#> 119.2 24.00 0 17 0 0
#> 64 24.00 0 43 0 0
#> 186 24.00 0 45 1 0
#> 7 24.00 0 37 1 0
#> 185 24.00 0 44 1 0
#> 191 24.00 0 60 0 1
#> 119.3 24.00 0 17 0 0
#> 87 24.00 0 27 0 0
#> 116 24.00 0 58 0 1
#> 20 24.00 0 46 1 0
#> 112.1 24.00 0 61 0 0
#> 82 24.00 0 34 0 0
#> 83 24.00 0 6 0 0
#> 72 24.00 0 40 0 1
#> 160 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 198 24.00 0 66 0 1
#> 132 24.00 0 55 0 0
#> 73 24.00 0 NA 0 1
#> 28 24.00 0 67 1 0
#> 74 24.00 0 43 0 1
#> 152 24.00 0 36 0 1
#> 44.1 24.00 0 56 0 0
#> 146 24.00 0 63 1 0
#> 172.1 24.00 0 41 0 0
#> 185.1 24.00 0 44 1 0
#> 34.1 24.00 0 36 0 0
#> 80 24.00 0 41 0 0
#> 112.2 24.00 0 61 0 0
#> 104 24.00 0 50 1 0
#> 144.1 24.00 0 28 0 1
#> 185.2 24.00 0 44 1 0
#> 54.1 24.00 0 53 1 0
#> 17.2 24.00 0 38 0 1
#> 186.1 24.00 0 45 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.58 NA NA NA
#> 2 age, Cure model 0.0261 NA NA NA
#> 3 grade_ii, Cure model 0.516 NA NA NA
#> 4 grade_iii, Cure model 0.937 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000821 NA NA NA
#> 2 grade_ii, Survival model 0.652 NA NA NA
#> 3 grade_iii, Survival model 0.488 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.57973 0.02607 0.51572 0.93664
#>
#> Degrees of Freedom: 183 Total (i.e. Null); 180 Residual
#> Null Deviance: 254.5
#> Residual Deviance: 241.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.57973213 0.02607299 0.51572334 0.93664016
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0008214519 0.6518281444 0.4875132089
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.21639922 0.24354477 0.40022655 0.78263098 0.81351330 0.69358326
#> [7] 0.09203977 0.13636567 0.33241785 0.60754344 0.49407835 0.37787090
#> [13] 0.75062429 0.37787090 0.64281473 0.84399743 0.92444813 0.76672268
#> [19] 0.27079882 0.35556663 0.47374159 0.92444813 0.18612203 0.82124001
#> [25] 0.57165588 0.57165588 0.52406675 0.75062429 0.43229871 0.61645805
#> [31] 0.92444813 0.30853156 0.50424345 0.83638580 0.53379833 0.27079882
#> [37] 0.57165588 0.54354095 0.40022655 0.67698645 0.95214078 0.33241785
#> [43] 0.70985180 0.82124001 0.91725881 0.79055634 0.96598061 0.35556663
#> [49] 0.51423594 0.97965050 0.46319777 0.96598061 0.98648357 0.02463247
#> [55] 0.64281473 0.79055634 0.15501309 0.62537886 0.87389703 0.11531781
#> [61] 0.56228992 0.85155243 0.76672268 0.72613449 0.90275368 0.74242813
#> [67] 0.54354095 0.87389703 0.62537886 0.42161976 0.95214078 0.69358326
#> [73] 0.70985180 0.43229871 0.79055634 0.98648357 0.67698645 0.15501309
#> [79] 0.02463247 0.92444813 0.21639922 0.29597319 0.65987296 0.72613449
#> [85] 0.85906980 0.85906980 0.32066454 0.43229871 0.24354477 0.59855393
#> [91] 0.87389703 0.91002303 0.66846144 0.87389703 0.06911509 0.20123835
#> [97] 0.47374159 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 194 175 158 60 14 18 168 129 68 188 51 150 96
#> 22.40 21.91 20.14 13.15 12.89 15.21 23.72 23.41 20.62 16.16 18.23 20.33 14.54
#> 150.1 125 37 187 57 139 128 108 187.1 63 140 85 192
#> 20.33 15.65 12.52 9.92 14.46 21.49 20.35 18.29 9.92 22.77 12.68 16.44 16.44
#> 110 96.1 58 100 187.2 32 41 177 30 139.1 192.1 106 158.1
#> 17.56 14.54 19.34 16.07 9.92 20.90 18.02 12.53 17.43 21.49 16.44 16.67 20.14
#> 167 16 68.1 157 140.1 145 123 149 128.1 134 77 8 149.1
#> 15.55 8.71 20.62 15.10 12.68 10.07 13.00 8.37 20.35 17.81 7.27 18.43 8.37
#> 91 24 125.1 123.1 92 26 159 164 130 42 57.1 180 93
#> 5.33 23.89 15.65 13.00 22.92 15.77 10.55 23.60 16.47 12.43 14.46 14.82 10.33
#> 133 106.1 159.1 26.1 170 16.1 18.1 157.1 55 123.2 91.1 167.1 92.1
#> 14.65 16.67 10.55 15.77 19.54 8.71 15.21 15.10 19.34 13.00 5.33 15.55 22.92
#> 24.1 187.3 194.1 36 6 180.1 43 43.1 190 58.1 175.1 79 159.2
#> 23.89 9.92 22.40 21.19 15.64 14.82 12.10 12.10 20.81 19.34 21.91 16.23 10.55
#> 61 39 159.3 86 15 108.1 102 17 131 84 137 156 126
#> 10.12 15.59 10.55 23.81 22.68 18.29 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84.1 34 131.1 3 196 178 17.1 2 3.1 103 200 193 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2.1 176 173 162 165 151 112 172 193.1 119 120 144 156.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 182 182.1 54 9 71 109 44 94 48 178.1 176.1 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163.1 174 174.1 182.2 119.1 103.1 98 119.2 64 186 7 185 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119.3 87 116 20 112.1 82 83 72 160 53 198 132 28
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74 152 44.1 146 172.1 185.1 34.1 80 112.2 104 144.1 185.2 54.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17.2 186.1
#> 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[13]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.000767307 0.673166952 0.422552249
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.02470658 0.01754841 0.34516734
#> grade_iii, Cure model
#> 0.85607721
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 189 10.51 1 NA 1 0
#> 29 15.45 1 68 1 0
#> 154 12.63 1 20 1 0
#> 52 10.42 1 52 0 1
#> 91 5.33 1 61 0 1
#> 88 18.37 1 47 0 0
#> 181 16.46 1 45 0 1
#> 37 12.52 1 57 1 0
#> 181.1 16.46 1 45 0 1
#> 180 14.82 1 37 0 0
#> 168 23.72 1 70 0 0
#> 68 20.62 1 44 0 0
#> 99 21.19 1 38 0 1
#> 127 3.53 1 62 0 1
#> 184 17.77 1 38 0 0
#> 180.1 14.82 1 37 0 0
#> 100 16.07 1 60 0 0
#> 76 19.22 1 54 0 1
#> 117 17.46 1 26 0 1
#> 195 11.76 1 NA 1 0
#> 79 16.23 1 54 1 0
#> 49 12.19 1 48 1 0
#> 5 16.43 1 51 0 1
#> 60 13.15 1 38 1 0
#> 197 21.60 1 69 1 0
#> 88.1 18.37 1 47 0 0
#> 140 12.68 1 59 1 0
#> 52.1 10.42 1 52 0 1
#> 170 19.54 1 43 0 1
#> 58 19.34 1 39 0 0
#> 91.1 5.33 1 61 0 1
#> 175 21.91 1 43 0 0
#> 40 18.00 1 28 1 0
#> 58.1 19.34 1 39 0 0
#> 60.1 13.15 1 38 1 0
#> 43 12.10 1 61 0 1
#> 90 20.94 1 50 0 1
#> 194 22.40 1 38 0 1
#> 23 16.92 1 61 0 0
#> 170.1 19.54 1 43 0 1
#> 81 14.06 1 34 0 0
#> 79.1 16.23 1 54 1 0
#> 153 21.33 1 55 1 0
#> 50 10.02 1 NA 1 0
#> 55 19.34 1 69 0 1
#> 49.1 12.19 1 48 1 0
#> 183 9.24 1 67 1 0
#> 16 8.71 1 71 0 1
#> 99.1 21.19 1 38 0 1
#> 24 23.89 1 38 0 0
#> 40.1 18.00 1 28 1 0
#> 155 13.08 1 26 0 0
#> 175.1 21.91 1 43 0 0
#> 49.2 12.19 1 48 1 0
#> 158 20.14 1 74 1 0
#> 92 22.92 1 47 0 1
#> 52.2 10.42 1 52 0 1
#> 16.1 8.71 1 71 0 1
#> 117.1 17.46 1 26 0 1
#> 184.1 17.77 1 38 0 0
#> 199 19.81 1 NA 0 1
#> 57 14.46 1 45 0 1
#> 171 16.57 1 41 0 1
#> 29.1 15.45 1 68 1 0
#> 154.1 12.63 1 20 1 0
#> 187 9.92 1 39 1 0
#> 159 10.55 1 50 0 1
#> 91.2 5.33 1 61 0 1
#> 179 18.63 1 42 0 0
#> 164 23.60 1 76 0 1
#> 169 22.41 1 46 0 0
#> 125 15.65 1 67 1 0
#> 29.2 15.45 1 68 1 0
#> 125.1 15.65 1 67 1 0
#> 52.3 10.42 1 52 0 1
#> 167 15.55 1 56 1 0
#> 150 20.33 1 48 0 0
#> 145 10.07 1 65 1 0
#> 97 19.14 1 65 0 1
#> 76.1 19.22 1 54 0 1
#> 97.1 19.14 1 65 0 1
#> 105 19.75 1 60 0 0
#> 6 15.64 1 39 0 0
#> 154.2 12.63 1 20 1 0
#> 77 7.27 1 67 0 1
#> 140.1 12.68 1 59 1 0
#> 197.1 21.60 1 69 1 0
#> 155.1 13.08 1 26 0 0
#> 81.1 14.06 1 34 0 0
#> 190 20.81 1 42 1 0
#> 177 12.53 1 75 0 0
#> 37.1 12.52 1 57 1 0
#> 37.2 12.52 1 57 1 0
#> 139 21.49 1 63 1 0
#> 133 14.65 1 57 0 0
#> 149 8.37 1 33 1 0
#> 51 18.23 1 83 0 1
#> 107 11.18 1 54 1 0
#> 130 16.47 1 53 0 1
#> 180.2 14.82 1 37 0 0
#> 177.1 12.53 1 75 0 0
#> 134 17.81 1 47 1 0
#> 181.2 16.46 1 45 0 1
#> 4 17.64 1 NA 0 1
#> 192 16.44 1 31 1 0
#> 63 22.77 1 31 1 0
#> 145.1 10.07 1 65 1 0
#> 108 18.29 1 39 0 1
#> 24.1 23.89 1 38 0 0
#> 79.2 16.23 1 54 1 0
#> 50.1 10.02 1 NA 1 0
#> 189.1 10.51 1 NA 1 0
#> 118 24.00 0 44 1 0
#> 67 24.00 0 25 0 0
#> 162 24.00 0 51 0 0
#> 146 24.00 0 63 1 0
#> 22 24.00 0 52 1 0
#> 47 24.00 0 38 0 1
#> 1 24.00 0 23 1 0
#> 137 24.00 0 45 1 0
#> 193 24.00 0 45 0 1
#> 46 24.00 0 71 0 0
#> 143 24.00 0 51 0 0
#> 73 24.00 0 NA 0 1
#> 156 24.00 0 50 1 0
#> 116 24.00 0 58 0 1
#> 141 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 196 24.00 0 19 0 0
#> 185 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 34 24.00 0 36 0 0
#> 109 24.00 0 48 0 0
#> 122 24.00 0 66 0 0
#> 7.1 24.00 0 37 1 0
#> 3 24.00 0 31 1 0
#> 165 24.00 0 47 0 0
#> 138 24.00 0 44 1 0
#> 44 24.00 0 56 0 0
#> 137.1 24.00 0 45 1 0
#> 176 24.00 0 43 0 1
#> 172 24.00 0 41 0 0
#> 162.1 24.00 0 51 0 0
#> 144 24.00 0 28 0 1
#> 132 24.00 0 55 0 0
#> 71 24.00 0 51 0 0
#> 176.1 24.00 0 43 0 1
#> 119 24.00 0 17 0 0
#> 31 24.00 0 36 0 1
#> 160 24.00 0 31 1 0
#> 82 24.00 0 34 0 0
#> 126 24.00 0 48 0 0
#> 9 24.00 0 31 1 0
#> 82.1 24.00 0 34 0 0
#> 35 24.00 0 51 0 0
#> 143.1 24.00 0 51 0 0
#> 193.1 24.00 0 45 0 1
#> 38 24.00 0 31 1 0
#> 156.1 24.00 0 50 1 0
#> 143.2 24.00 0 51 0 0
#> 64 24.00 0 43 0 0
#> 31.1 24.00 0 36 0 1
#> 162.2 24.00 0 51 0 0
#> 156.2 24.00 0 50 1 0
#> 135 24.00 0 58 1 0
#> 200 24.00 0 64 0 0
#> 143.3 24.00 0 51 0 0
#> 121 24.00 0 57 1 0
#> 198 24.00 0 66 0 1
#> 122.1 24.00 0 66 0 0
#> 162.3 24.00 0 51 0 0
#> 165.1 24.00 0 47 0 0
#> 82.2 24.00 0 34 0 0
#> 160.1 24.00 0 31 1 0
#> 196.1 24.00 0 19 0 0
#> 121.1 24.00 0 57 1 0
#> 83 24.00 0 6 0 0
#> 64.1 24.00 0 43 0 0
#> 141.1 24.00 0 44 1 0
#> 193.2 24.00 0 45 0 1
#> 141.2 24.00 0 44 1 0
#> 94 24.00 0 51 0 1
#> 47.1 24.00 0 38 0 1
#> 191 24.00 0 60 0 1
#> 186 24.00 0 45 1 0
#> 160.2 24.00 0 31 1 0
#> 156.3 24.00 0 50 1 0
#> 103 24.00 0 56 1 0
#> 112 24.00 0 61 0 0
#> 200.1 24.00 0 64 0 0
#> 146.1 24.00 0 63 1 0
#> 102 24.00 0 49 0 0
#> 112.1 24.00 0 61 0 0
#> 185.1 24.00 0 44 1 0
#> 178 24.00 0 52 1 0
#> 17 24.00 0 38 0 1
#> 198.1 24.00 0 66 0 1
#> 95 24.00 0 68 0 1
#> 116.1 24.00 0 58 0 1
#> 103.1 24.00 0 56 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.02 NA NA NA
#> 2 age, Cure model 0.0175 NA NA NA
#> 3 grade_ii, Cure model 0.345 NA NA NA
#> 4 grade_iii, Cure model 0.856 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000767 NA NA NA
#> 2 grade_ii, Survival model 0.673 NA NA NA
#> 3 grade_iii, Survival model 0.423 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.02471 0.01755 0.34517 0.85608
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.5
#> Residual Deviance: 255.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.02470658 0.01754841 0.34516734 0.85607721
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.000767307 0.673166952 0.422552249
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.69495854 0.81017764 0.90263422 0.97635023 0.46513155 0.59163354
#> [7] 0.84413334 0.59163354 0.71678148 0.06921484 0.32142541 0.27491284
#> [13] 0.99407689 0.53037537 0.71678148 0.65643992 0.41646638 0.54811430
#> [19] 0.63302052 0.86396232 0.62479426 0.76773222 0.22151228 0.46513155
#> [25] 0.79620595 0.90263422 0.36568085 0.38637514 0.97635023 0.18991505
#> [31] 0.50335012 0.38637514 0.76773222 0.88333169 0.29842218 0.17330811
#> [37] 0.56553943 0.36568085 0.75321861 0.63302052 0.26226491 0.38637514
#> [43] 0.86396232 0.94608079 0.95220058 0.27491284 0.02620505 0.50335012
#> [49] 0.78197169 0.18991505 0.86396232 0.34395051 0.11787726 0.90263422
#> [55] 0.95220058 0.54811430 0.53037537 0.74592278 0.57431363 0.69495854
#> [61] 0.81017764 0.93991859 0.89623423 0.97635023 0.45542609 0.09542200
#> [67] 0.15574222 0.66433663 0.69495854 0.66433663 0.90263422 0.68734946
#> [73] 0.33269510 0.92755218 0.43620873 0.41646638 0.43620873 0.35482351
#> [79] 0.67965120 0.81017764 0.97033945 0.79620595 0.22151228 0.78197169
#> [85] 0.75321861 0.31014219 0.83052539 0.84413334 0.84413334 0.24894608
#> [91] 0.73858536 0.96430602 0.49388800 0.88980736 0.58301148 0.71678148
#> [97] 0.83052539 0.52142156 0.59163354 0.61650395 0.13810707 0.92755218
#> [103] 0.48431100 0.02620505 0.63302052 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 29 154 52 91 88 181 37 181.1 180 168 68 99 127
#> 15.45 12.63 10.42 5.33 18.37 16.46 12.52 16.46 14.82 23.72 20.62 21.19 3.53
#> 184 180.1 100 76 117 79 49 5 60 197 88.1 140 52.1
#> 17.77 14.82 16.07 19.22 17.46 16.23 12.19 16.43 13.15 21.60 18.37 12.68 10.42
#> 170 58 91.1 175 40 58.1 60.1 43 90 194 23 170.1 81
#> 19.54 19.34 5.33 21.91 18.00 19.34 13.15 12.10 20.94 22.40 16.92 19.54 14.06
#> 79.1 153 55 49.1 183 16 99.1 24 40.1 155 175.1 49.2 158
#> 16.23 21.33 19.34 12.19 9.24 8.71 21.19 23.89 18.00 13.08 21.91 12.19 20.14
#> 92 52.2 16.1 117.1 184.1 57 171 29.1 154.1 187 159 91.2 179
#> 22.92 10.42 8.71 17.46 17.77 14.46 16.57 15.45 12.63 9.92 10.55 5.33 18.63
#> 164 169 125 29.2 125.1 52.3 167 150 145 97 76.1 97.1 105
#> 23.60 22.41 15.65 15.45 15.65 10.42 15.55 20.33 10.07 19.14 19.22 19.14 19.75
#> 6 154.2 77 140.1 197.1 155.1 81.1 190 177 37.1 37.2 139 133
#> 15.64 12.63 7.27 12.68 21.60 13.08 14.06 20.81 12.53 12.52 12.52 21.49 14.65
#> 149 51 107 130 180.2 177.1 134 181.2 192 63 145.1 108 24.1
#> 8.37 18.23 11.18 16.47 14.82 12.53 17.81 16.46 16.44 22.77 10.07 18.29 23.89
#> 79.2 118 67 162 146 22 47 1 137 193 46 143 156
#> 16.23 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 141 7 196 185 65 34 109 122 7.1 3 165 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 137.1 176 172 162.1 144 132 71 176.1 119 31 160 82
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 9 82.1 35 143.1 193.1 38 156.1 143.2 64 31.1 162.2 156.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 200 143.3 121 198 122.1 162.3 165.1 82.2 160.1 196.1 121.1 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64.1 141.1 193.2 141.2 94 47.1 191 186 160.2 156.3 103 112 200.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146.1 102 112.1 185.1 178 17 198.1 95 116.1 103.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[14]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002073983 0.457269354 -0.009754151
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.18325391 0.01154473 0.51709692
#> grade_iii, Cure model
#> 1.52719816
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 150 20.33 1 48 0 0
#> 108 18.29 1 39 0 1
#> 59 10.16 1 NA 1 0
#> 150.1 20.33 1 48 0 0
#> 59.1 10.16 1 NA 1 0
#> 149 8.37 1 33 1 0
#> 111 17.45 1 47 0 1
#> 30 17.43 1 78 0 0
#> 164 23.60 1 76 0 1
#> 4 17.64 1 NA 0 1
#> 77 7.27 1 67 0 1
#> 150.2 20.33 1 48 0 0
#> 168 23.72 1 70 0 0
#> 134 17.81 1 47 1 0
#> 179 18.63 1 42 0 0
#> 111.1 17.45 1 47 0 1
#> 184 17.77 1 38 0 0
#> 125 15.65 1 67 1 0
#> 111.2 17.45 1 47 0 1
#> 187 9.92 1 39 1 0
#> 5 16.43 1 51 0 1
#> 159 10.55 1 50 0 1
#> 16 8.71 1 71 0 1
#> 192 16.44 1 31 1 0
#> 96 14.54 1 33 0 1
#> 154 12.63 1 20 1 0
#> 79 16.23 1 54 1 0
#> 91 5.33 1 61 0 1
#> 123 13.00 1 44 1 0
#> 180 14.82 1 37 0 0
#> 133 14.65 1 57 0 0
#> 4.1 17.64 1 NA 0 1
#> 177 12.53 1 75 0 0
#> 92 22.92 1 47 0 1
#> 145 10.07 1 65 1 0
#> 39 15.59 1 37 0 1
#> 154.1 12.63 1 20 1 0
#> 140 12.68 1 59 1 0
#> 194 22.40 1 38 0 1
#> 190 20.81 1 42 1 0
#> 155 13.08 1 26 0 0
#> 69 23.23 1 25 0 1
#> 124 9.73 1 NA 1 0
#> 89 11.44 1 NA 0 0
#> 108.1 18.29 1 39 0 1
#> 197 21.60 1 69 1 0
#> 57 14.46 1 45 0 1
#> 69.1 23.23 1 25 0 1
#> 45 17.42 1 54 0 1
#> 55 19.34 1 69 0 1
#> 106 16.67 1 49 1 0
#> 125.1 15.65 1 67 1 0
#> 42 12.43 1 49 0 1
#> 8 18.43 1 32 0 0
#> 32 20.90 1 37 1 0
#> 167 15.55 1 56 1 0
#> 4.2 17.64 1 NA 0 1
#> 183 9.24 1 67 1 0
#> 16.1 8.71 1 71 0 1
#> 89.1 11.44 1 NA 0 0
#> 134.1 17.81 1 47 1 0
#> 15 22.68 1 48 0 0
#> 55.1 19.34 1 69 0 1
#> 105 19.75 1 60 0 0
#> 101 9.97 1 10 0 1
#> 140.1 12.68 1 59 1 0
#> 114 13.68 1 NA 0 0
#> 66 22.13 1 53 0 0
#> 93 10.33 1 52 0 1
#> 55.2 19.34 1 69 0 1
#> 10 10.53 1 34 0 0
#> 130 16.47 1 53 0 1
#> 195 11.76 1 NA 1 0
#> 86 23.81 1 58 0 1
#> 97 19.14 1 65 0 1
#> 51 18.23 1 83 0 1
#> 96.1 14.54 1 33 0 1
#> 195.1 11.76 1 NA 1 0
#> 43 12.10 1 61 0 1
#> 124.1 9.73 1 NA 1 0
#> 89.2 11.44 1 NA 0 0
#> 91.1 5.33 1 61 0 1
#> 42.1 12.43 1 49 0 1
#> 136 21.83 1 43 0 1
#> 195.2 11.76 1 NA 1 0
#> 195.3 11.76 1 NA 1 0
#> 117 17.46 1 26 0 1
#> 89.3 11.44 1 NA 0 0
#> 159.1 10.55 1 50 0 1
#> 89.4 11.44 1 NA 0 0
#> 194.1 22.40 1 38 0 1
#> 97.1 19.14 1 65 0 1
#> 153 21.33 1 55 1 0
#> 129 23.41 1 53 1 0
#> 52 10.42 1 52 0 1
#> 85 16.44 1 36 0 0
#> 51.1 18.23 1 83 0 1
#> 69.2 23.23 1 25 0 1
#> 86.1 23.81 1 58 0 1
#> 92.1 22.92 1 47 0 1
#> 86.2 23.81 1 58 0 1
#> 40 18.00 1 28 1 0
#> 61 10.12 1 36 0 1
#> 125.2 15.65 1 67 1 0
#> 57.1 14.46 1 45 0 1
#> 39.1 15.59 1 37 0 1
#> 192.1 16.44 1 31 1 0
#> 159.2 10.55 1 50 0 1
#> 41 18.02 1 40 1 0
#> 69.3 23.23 1 25 0 1
#> 90 20.94 1 50 0 1
#> 169 22.41 1 46 0 0
#> 165 24.00 0 47 0 0
#> 144 24.00 0 28 0 1
#> 12 24.00 0 63 0 0
#> 53 24.00 0 32 0 1
#> 141 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 163 24.00 0 66 0 0
#> 142 24.00 0 53 0 0
#> 200 24.00 0 64 0 0
#> 186 24.00 0 45 1 0
#> 35 24.00 0 51 0 0
#> 152 24.00 0 36 0 1
#> 47 24.00 0 38 0 1
#> 11 24.00 0 42 0 1
#> 146 24.00 0 63 1 0
#> 67 24.00 0 25 0 0
#> 109 24.00 0 48 0 0
#> 7 24.00 0 37 1 0
#> 178 24.00 0 52 1 0
#> 31 24.00 0 36 0 1
#> 148 24.00 0 61 1 0
#> 112 24.00 0 61 0 0
#> 31.1 24.00 0 36 0 1
#> 75 24.00 0 21 1 0
#> 19 24.00 0 57 0 1
#> 148.1 24.00 0 61 1 0
#> 84 24.00 0 39 0 1
#> 137 24.00 0 45 1 0
#> 193 24.00 0 45 0 1
#> 143 24.00 0 51 0 0
#> 135 24.00 0 58 1 0
#> 72 24.00 0 40 0 1
#> 21 24.00 0 47 0 0
#> 3 24.00 0 31 1 0
#> 74 24.00 0 43 0 1
#> 54 24.00 0 53 1 0
#> 200.1 24.00 0 64 0 0
#> 54.1 24.00 0 53 1 0
#> 186.1 24.00 0 45 1 0
#> 19.1 24.00 0 57 0 1
#> 196 24.00 0 19 0 0
#> 103 24.00 0 56 1 0
#> 80 24.00 0 41 0 0
#> 21.1 24.00 0 47 0 0
#> 144.1 24.00 0 28 0 1
#> 65 24.00 0 57 1 0
#> 38 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 64 24.00 0 43 0 0
#> 72.1 24.00 0 40 0 1
#> 104 24.00 0 50 1 0
#> 112.1 24.00 0 61 0 0
#> 7.1 24.00 0 37 1 0
#> 151 24.00 0 42 0 0
#> 200.2 24.00 0 64 0 0
#> 165.1 24.00 0 47 0 0
#> 73 24.00 0 NA 0 1
#> 7.2 24.00 0 37 1 0
#> 186.2 24.00 0 45 1 0
#> 21.2 24.00 0 47 0 0
#> 102 24.00 0 49 0 0
#> 126 24.00 0 48 0 0
#> 115 24.00 0 NA 1 0
#> 182 24.00 0 35 0 0
#> 21.3 24.00 0 47 0 0
#> 72.2 24.00 0 40 0 1
#> 82 24.00 0 34 0 0
#> 131 24.00 0 66 0 0
#> 122 24.00 0 66 0 0
#> 143.1 24.00 0 51 0 0
#> 73.1 24.00 0 NA 0 1
#> 118 24.00 0 44 1 0
#> 71 24.00 0 51 0 0
#> 74.1 24.00 0 43 0 1
#> 46 24.00 0 71 0 0
#> 135.1 24.00 0 58 1 0
#> 118.1 24.00 0 44 1 0
#> 72.3 24.00 0 40 0 1
#> 82.1 24.00 0 34 0 0
#> 95 24.00 0 68 0 1
#> 115.1 24.00 0 NA 1 0
#> 147 24.00 0 76 1 0
#> 65.1 24.00 0 57 1 0
#> 19.2 24.00 0 57 0 1
#> 44 24.00 0 56 0 0
#> 115.2 24.00 0 NA 1 0
#> 9 24.00 0 31 1 0
#> 11.1 24.00 0 42 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.18 NA NA NA
#> 2 age, Cure model 0.0115 NA NA NA
#> 3 grade_ii, Cure model 0.517 NA NA NA
#> 4 grade_iii, Cure model 1.53 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00207 NA NA NA
#> 2 grade_ii, Survival model 0.457 NA NA NA
#> 3 grade_iii, Survival model -0.00975 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.18325 0.01154 0.51710 1.52720
#>
#> Degrees of Freedom: 177 Total (i.e. Null); 174 Residual
#> Null Deviance: 246
#> Residual Deviance: 228.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.18325391 0.01154473 0.51709692 1.52719816
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002073983 0.457269354 -0.009754151
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.25369852 0.37066045 0.25369852 0.95998849 0.47894656 0.51053829
#> [7] 0.04830235 0.96999331 0.25369852 0.03629526 0.43648863 0.34862286
#> [13] 0.47894656 0.45756693 0.60577117 0.47894656 0.91989473 0.58470117
#> [19] 0.82912878 0.93998456 0.55361125 0.68738260 0.76910779 0.59527461
#> [25] 0.98001242 0.73866139 0.66684766 0.67710645 0.78901637 0.11009588
#> [31] 0.89966645 0.63613737 0.76910779 0.74892998 0.15385711 0.24306138
#> [37] 0.72832933 0.07232997 0.37066045 0.19881978 0.70782695 0.07232997
#> [43] 0.52132783 0.29541085 0.53214303 0.60577117 0.79905261 0.35963080
#> [49] 0.23221164 0.65660052 0.92995998 0.93998456 0.43648863 0.13137595
#> [55] 0.29541085 0.28464848 0.90977890 0.74892998 0.17586045 0.87936406
#> [61] 0.29541085 0.85911008 0.54286517 0.01162092 0.32701061 0.39250284
#> [67] 0.68738260 0.81905168 0.98001242 0.79905261 0.18730688 0.46824921
#> [73] 0.82912878 0.15385711 0.32701061 0.21009200 0.06080270 0.86923052
#> [79] 0.55361125 0.39250284 0.07232997 0.01162092 0.11009588 0.01162092
#> [85] 0.42558843 0.88951056 0.60577117 0.70782695 0.63613737 0.55361125
#> [91] 0.82912878 0.41454954 0.07232997 0.22112210 0.14257600 0.00000000
#> [97] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 150 108 150.1 149 111 30 164 77 150.2 168 134 179 111.1
#> 20.33 18.29 20.33 8.37 17.45 17.43 23.60 7.27 20.33 23.72 17.81 18.63 17.45
#> 184 125 111.2 187 5 159 16 192 96 154 79 91 123
#> 17.77 15.65 17.45 9.92 16.43 10.55 8.71 16.44 14.54 12.63 16.23 5.33 13.00
#> 180 133 177 92 145 39 154.1 140 194 190 155 69 108.1
#> 14.82 14.65 12.53 22.92 10.07 15.59 12.63 12.68 22.40 20.81 13.08 23.23 18.29
#> 197 57 69.1 45 55 106 125.1 42 8 32 167 183 16.1
#> 21.60 14.46 23.23 17.42 19.34 16.67 15.65 12.43 18.43 20.90 15.55 9.24 8.71
#> 134.1 15 55.1 105 101 140.1 66 93 55.2 10 130 86 97
#> 17.81 22.68 19.34 19.75 9.97 12.68 22.13 10.33 19.34 10.53 16.47 23.81 19.14
#> 51 96.1 43 91.1 42.1 136 117 159.1 194.1 97.1 153 129 52
#> 18.23 14.54 12.10 5.33 12.43 21.83 17.46 10.55 22.40 19.14 21.33 23.41 10.42
#> 85 51.1 69.2 86.1 92.1 86.2 40 61 125.2 57.1 39.1 192.1 159.2
#> 16.44 18.23 23.23 23.81 22.92 23.81 18.00 10.12 15.65 14.46 15.59 16.44 10.55
#> 41 69.3 90 169 165 144 12 53 141 27 163 142 200
#> 18.02 23.23 20.94 22.41 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 35 152 47 11 146 67 109 7 178 31 148 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31.1 75 19 148.1 84 137 193 143 135 72 21 3 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 200.1 54.1 186.1 19.1 196 103 80 21.1 144.1 65 38 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 72.1 104 112.1 7.1 151 200.2 165.1 7.2 186.2 21.2 102 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 21.3 72.2 82 131 122 143.1 118 71 74.1 46 135.1 118.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.3 82.1 95 147 65.1 19.2 44 9 11.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[15]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003788024 0.316182889 0.235113239
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.031332217 -0.002393656 0.151265227
#> grade_iii, Cure model
#> 0.554051488
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 158 20.14 1 74 1 0
#> 190 20.81 1 42 1 0
#> 39 15.59 1 37 0 1
#> 110 17.56 1 65 0 1
#> 195 11.76 1 NA 1 0
#> 192 16.44 1 31 1 0
#> 25 6.32 1 34 1 0
#> 78 23.88 1 43 0 0
#> 4 17.64 1 NA 0 1
#> 107 11.18 1 54 1 0
#> 69 23.23 1 25 0 1
#> 52 10.42 1 52 0 1
#> 171 16.57 1 41 0 1
#> 66 22.13 1 53 0 0
#> 133 14.65 1 57 0 0
#> 59 10.16 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 158.1 20.14 1 74 1 0
#> 90 20.94 1 50 0 1
#> 175 21.91 1 43 0 0
#> 6 15.64 1 39 0 0
#> 77 7.27 1 67 0 1
#> 128 20.35 1 35 0 1
#> 86 23.81 1 58 0 1
#> 14 12.89 1 21 0 0
#> 106 16.67 1 49 1 0
#> 77.1 7.27 1 67 0 1
#> 110.1 17.56 1 65 0 1
#> 15 22.68 1 48 0 0
#> 99 21.19 1 38 0 1
#> 77.2 7.27 1 67 0 1
#> 154 12.63 1 20 1 0
#> 86.1 23.81 1 58 0 1
#> 40 18.00 1 28 1 0
#> 188 16.16 1 46 0 1
#> 159 10.55 1 50 0 1
#> 88 18.37 1 47 0 0
#> 30 17.43 1 78 0 0
#> 14.1 12.89 1 21 0 0
#> 86.2 23.81 1 58 0 1
#> 140 12.68 1 59 1 0
#> 129 23.41 1 53 1 0
#> 195.1 11.76 1 NA 1 0
#> 129.1 23.41 1 53 1 0
#> 194 22.40 1 38 0 1
#> 15.1 22.68 1 48 0 0
#> 41 18.02 1 40 1 0
#> 81 14.06 1 34 0 0
#> 114 13.68 1 NA 0 0
#> 4.1 17.64 1 NA 0 1
#> 111.1 17.45 1 47 0 1
#> 51 18.23 1 83 0 1
#> 70 7.38 1 30 1 0
#> 18 15.21 1 49 1 0
#> 50 10.02 1 NA 1 0
#> 5 16.43 1 51 0 1
#> 6.1 15.64 1 39 0 0
#> 125 15.65 1 67 1 0
#> 36 21.19 1 48 0 1
#> 51.1 18.23 1 83 0 1
#> 123 13.00 1 44 1 0
#> 66.1 22.13 1 53 0 0
#> 8 18.43 1 32 0 0
#> 101 9.97 1 10 0 1
#> 63 22.77 1 31 1 0
#> 45 17.42 1 54 0 1
#> 181 16.46 1 45 0 1
#> 145 10.07 1 65 1 0
#> 125.1 15.65 1 67 1 0
#> 63.1 22.77 1 31 1 0
#> 24 23.89 1 38 0 0
#> 79 16.23 1 54 1 0
#> 39.1 15.59 1 37 0 1
#> 117 17.46 1 26 0 1
#> 13 14.34 1 54 0 1
#> 93 10.33 1 52 0 1
#> 93.1 10.33 1 52 0 1
#> 197 21.60 1 69 1 0
#> 136 21.83 1 43 0 1
#> 66.2 22.13 1 53 0 0
#> 56 12.21 1 60 0 0
#> 164 23.60 1 76 0 1
#> 77.3 7.27 1 67 0 1
#> 14.2 12.89 1 21 0 0
#> 69.1 23.23 1 25 0 1
#> 184 17.77 1 38 0 0
#> 139 21.49 1 63 1 0
#> 99.1 21.19 1 38 0 1
#> 197.1 21.60 1 69 1 0
#> 10 10.53 1 34 0 0
#> 124 9.73 1 NA 1 0
#> 18.1 15.21 1 49 1 0
#> 14.3 12.89 1 21 0 0
#> 199 19.81 1 NA 0 1
#> 114.1 13.68 1 NA 0 0
#> 181.1 16.46 1 45 0 1
#> 57 14.46 1 45 0 1
#> 13.1 14.34 1 54 0 1
#> 107.1 11.18 1 54 1 0
#> 175.1 21.91 1 43 0 0
#> 79.1 16.23 1 54 1 0
#> 41.1 18.02 1 40 1 0
#> 50.1 10.02 1 NA 1 0
#> 197.2 21.60 1 69 1 0
#> 100 16.07 1 60 0 0
#> 190.1 20.81 1 42 1 0
#> 49 12.19 1 48 1 0
#> 23 16.92 1 61 0 0
#> 93.2 10.33 1 52 0 1
#> 5.1 16.43 1 51 0 1
#> 5.2 16.43 1 51 0 1
#> 158.2 20.14 1 74 1 0
#> 151 24.00 0 42 0 0
#> 104 24.00 0 50 1 0
#> 74 24.00 0 43 0 1
#> 112 24.00 0 61 0 0
#> 34 24.00 0 36 0 0
#> 95 24.00 0 68 0 1
#> 141 24.00 0 44 1 0
#> 19 24.00 0 57 0 1
#> 28 24.00 0 67 1 0
#> 11 24.00 0 42 0 1
#> 34.1 24.00 0 36 0 0
#> 65 24.00 0 57 1 0
#> 73 24.00 0 NA 0 1
#> 53 24.00 0 32 0 1
#> 1 24.00 0 23 1 0
#> 73.1 24.00 0 NA 0 1
#> 75 24.00 0 21 1 0
#> 121 24.00 0 57 1 0
#> 178 24.00 0 52 1 0
#> 84 24.00 0 39 0 1
#> 95.1 24.00 0 68 0 1
#> 176 24.00 0 43 0 1
#> 47 24.00 0 38 0 1
#> 21 24.00 0 47 0 0
#> 172 24.00 0 41 0 0
#> 80 24.00 0 41 0 0
#> 62 24.00 0 71 0 0
#> 28.1 24.00 0 67 1 0
#> 94 24.00 0 51 0 1
#> 135 24.00 0 58 1 0
#> 27 24.00 0 63 1 0
#> 7 24.00 0 37 1 0
#> 38 24.00 0 31 1 0
#> 121.1 24.00 0 57 1 0
#> 82 24.00 0 34 0 0
#> 146 24.00 0 63 1 0
#> 98 24.00 0 34 1 0
#> 73.2 24.00 0 NA 0 1
#> 94.1 24.00 0 51 0 1
#> 103 24.00 0 56 1 0
#> 147 24.00 0 76 1 0
#> 120 24.00 0 68 0 1
#> 80.1 24.00 0 41 0 0
#> 47.1 24.00 0 38 0 1
#> 3 24.00 0 31 1 0
#> 102 24.00 0 49 0 0
#> 72 24.00 0 40 0 1
#> 135.1 24.00 0 58 1 0
#> 143 24.00 0 51 0 0
#> 47.2 24.00 0 38 0 1
#> 156 24.00 0 50 1 0
#> 102.1 24.00 0 49 0 0
#> 12 24.00 0 63 0 0
#> 191 24.00 0 60 0 1
#> 104.1 24.00 0 50 1 0
#> 104.2 24.00 0 50 1 0
#> 148 24.00 0 61 1 0
#> 7.1 24.00 0 37 1 0
#> 193 24.00 0 45 0 1
#> 176.1 24.00 0 43 0 1
#> 3.1 24.00 0 31 1 0
#> 147.1 24.00 0 76 1 0
#> 21.1 24.00 0 47 0 0
#> 126 24.00 0 48 0 0
#> 7.2 24.00 0 37 1 0
#> 71 24.00 0 51 0 0
#> 138 24.00 0 44 1 0
#> 95.2 24.00 0 68 0 1
#> 19.1 24.00 0 57 0 1
#> 95.3 24.00 0 68 0 1
#> 119 24.00 0 17 0 0
#> 196 24.00 0 19 0 0
#> 193.1 24.00 0 45 0 1
#> 161 24.00 0 45 0 0
#> 44 24.00 0 56 0 0
#> 198 24.00 0 66 0 1
#> 148.1 24.00 0 61 1 0
#> 200 24.00 0 64 0 0
#> 72.1 24.00 0 40 0 1
#> 143.1 24.00 0 51 0 0
#> 120.1 24.00 0 68 0 1
#> 44.1 24.00 0 56 0 0
#> 163 24.00 0 66 0 0
#> 173 24.00 0 19 0 1
#> 143.2 24.00 0 51 0 0
#> 182 24.00 0 35 0 0
#> 116 24.00 0 58 0 1
#> 3.2 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.0313 NA NA NA
#> 2 age, Cure model -0.00239 NA NA NA
#> 3 grade_ii, Cure model 0.151 NA NA NA
#> 4 grade_iii, Cure model 0.554 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00379 NA NA NA
#> 2 grade_ii, Survival model 0.316 NA NA NA
#> 3 grade_iii, Survival model 0.235 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.031332 -0.002394 0.151265 0.554051
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.5
#> Residual Deviance: 254 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.031332217 -0.002393656 0.151265227 0.554051488
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003788024 0.316182889 0.235113239
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.330539979 0.300899474 0.672639205 0.438493157 0.556383803 0.990403368
#> [7] 0.017934484 0.846610289 0.092394692 0.885213310 0.526980122 0.161176245
#> [13] 0.711285446 0.467931374 0.330539979 0.290779487 0.190559637 0.653222850
#> [19] 0.952496575 0.320578270 0.032124003 0.769496319 0.517087095 0.952496575
#> [25] 0.438493157 0.131443806 0.261417875 0.952496575 0.817487465 0.032124003
#> [31] 0.418735205 0.614390679 0.865856312 0.369378476 0.487402280 0.769496319
#> [37] 0.032124003 0.807758535 0.071856463 0.071856463 0.151080696 0.131443806
#> [43] 0.399133485 0.750053184 0.467931374 0.379358162 0.942882313 0.691999935
#> [49] 0.566195834 0.653222850 0.633885470 0.261417875 0.379358162 0.759784780
#> [55] 0.161176245 0.359442584 0.933245992 0.112287070 0.497287987 0.536857749
#> [61] 0.923587929 0.633885470 0.112287070 0.005651409 0.595061939 0.672639205
#> [67] 0.458068182 0.730746331 0.894894158 0.894894158 0.221466854 0.211016514
#> [73] 0.161176245 0.827185029 0.060313966 0.952496575 0.769496319 0.092394692
#> [79] 0.428598913 0.251142525 0.261417875 0.221466854 0.875528346 0.691999935
#> [85] 0.769496319 0.536857749 0.721020273 0.730746331 0.846610289 0.190559637
#> [91] 0.595061939 0.399133485 0.221466854 0.624122598 0.300899474 0.836905763
#> [97] 0.507167605 0.894894158 0.566195834 0.566195834 0.330539979 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 158 190 39 110 192 25 78 107 69 52 171 66 133
#> 20.14 20.81 15.59 17.56 16.44 6.32 23.88 11.18 23.23 10.42 16.57 22.13 14.65
#> 111 158.1 90 175 6 77 128 86 14 106 77.1 110.1 15
#> 17.45 20.14 20.94 21.91 15.64 7.27 20.35 23.81 12.89 16.67 7.27 17.56 22.68
#> 99 77.2 154 86.1 40 188 159 88 30 14.1 86.2 140 129
#> 21.19 7.27 12.63 23.81 18.00 16.16 10.55 18.37 17.43 12.89 23.81 12.68 23.41
#> 129.1 194 15.1 41 81 111.1 51 70 18 5 6.1 125 36
#> 23.41 22.40 22.68 18.02 14.06 17.45 18.23 7.38 15.21 16.43 15.64 15.65 21.19
#> 51.1 123 66.1 8 101 63 45 181 145 125.1 63.1 24 79
#> 18.23 13.00 22.13 18.43 9.97 22.77 17.42 16.46 10.07 15.65 22.77 23.89 16.23
#> 39.1 117 13 93 93.1 197 136 66.2 56 164 77.3 14.2 69.1
#> 15.59 17.46 14.34 10.33 10.33 21.60 21.83 22.13 12.21 23.60 7.27 12.89 23.23
#> 184 139 99.1 197.1 10 18.1 14.3 181.1 57 13.1 107.1 175.1 79.1
#> 17.77 21.49 21.19 21.60 10.53 15.21 12.89 16.46 14.46 14.34 11.18 21.91 16.23
#> 41.1 197.2 100 190.1 49 23 93.2 5.1 5.2 158.2 151 104 74
#> 18.02 21.60 16.07 20.81 12.19 16.92 10.33 16.43 16.43 20.14 24.00 24.00 24.00
#> 112 34 95 141 19 28 11 34.1 65 53 1 75 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 84 95.1 176 47 21 172 80 62 28.1 94 135 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 38 121.1 82 146 98 94.1 103 147 120 80.1 47.1 3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 72 135.1 143 47.2 156 102.1 12 191 104.1 104.2 148 7.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 176.1 3.1 147.1 21.1 126 7.2 71 138 95.2 19.1 95.3 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 193.1 161 44 198 148.1 200 72.1 143.1 120.1 44.1 163 173
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143.2 182 116 3.2
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[16]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.005119782 0.419262408 0.448404961
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.4783725 0.0149831 -0.1649353
#> grade_iii, Cure model
#> 0.1362228
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 129 23.41 1 53 1 0
#> 108 18.29 1 39 0 1
#> 140 12.68 1 59 1 0
#> 32 20.90 1 37 1 0
#> 177 12.53 1 75 0 0
#> 42 12.43 1 49 0 1
#> 30 17.43 1 78 0 0
#> 14 12.89 1 21 0 0
#> 195 11.76 1 NA 1 0
#> 113 22.86 1 34 0 0
#> 190 20.81 1 42 1 0
#> 195.1 11.76 1 NA 1 0
#> 99 21.19 1 38 0 1
#> 24 23.89 1 38 0 0
#> 124 9.73 1 NA 1 0
#> 154 12.63 1 20 1 0
#> 150 20.33 1 48 0 0
#> 49 12.19 1 48 1 0
#> 91 5.33 1 61 0 1
#> 91.1 5.33 1 61 0 1
#> 168 23.72 1 70 0 0
#> 192 16.44 1 31 1 0
#> 43 12.10 1 61 0 1
#> 30.1 17.43 1 78 0 0
#> 69 23.23 1 25 0 1
#> 192.1 16.44 1 31 1 0
#> 26 15.77 1 49 0 1
#> 37 12.52 1 57 1 0
#> 158 20.14 1 74 1 0
#> 51 18.23 1 83 0 1
#> 169 22.41 1 46 0 0
#> 39 15.59 1 37 0 1
#> 40 18.00 1 28 1 0
#> 133 14.65 1 57 0 0
#> 60 13.15 1 38 1 0
#> 8 18.43 1 32 0 0
#> 140.1 12.68 1 59 1 0
#> 69.1 23.23 1 25 0 1
#> 107 11.18 1 54 1 0
#> 85 16.44 1 36 0 0
#> 192.2 16.44 1 31 1 0
#> 184 17.77 1 38 0 0
#> 4 17.64 1 NA 0 1
#> 130 16.47 1 53 0 1
#> 184.1 17.77 1 38 0 0
#> 180 14.82 1 37 0 0
#> 184.2 17.77 1 38 0 0
#> 139 21.49 1 63 1 0
#> 168.1 23.72 1 70 0 0
#> 79 16.23 1 54 1 0
#> 195.2 11.76 1 NA 1 0
#> 26.1 15.77 1 49 0 1
#> 8.1 18.43 1 32 0 0
#> 13 14.34 1 54 0 1
#> 183 9.24 1 67 1 0
#> 106 16.67 1 49 1 0
#> 195.3 11.76 1 NA 1 0
#> 55 19.34 1 69 0 1
#> 108.1 18.29 1 39 0 1
#> 78 23.88 1 43 0 0
#> 170 19.54 1 43 0 1
#> 8.2 18.43 1 32 0 0
#> 32.1 20.90 1 37 1 0
#> 32.2 20.90 1 37 1 0
#> 175 21.91 1 43 0 0
#> 93 10.33 1 52 0 1
#> 81 14.06 1 34 0 0
#> 63 22.77 1 31 1 0
#> 90 20.94 1 50 0 1
#> 86 23.81 1 58 0 1
#> 175.1 21.91 1 43 0 0
#> 36 21.19 1 48 0 1
#> 197 21.60 1 69 1 0
#> 52 10.42 1 52 0 1
#> 37.1 12.52 1 57 1 0
#> 105 19.75 1 60 0 0
#> 117 17.46 1 26 0 1
#> 30.2 17.43 1 78 0 0
#> 85.1 16.44 1 36 0 0
#> 180.1 14.82 1 37 0 0
#> 127 3.53 1 62 0 1
#> 167 15.55 1 56 1 0
#> 154.1 12.63 1 20 1 0
#> 23 16.92 1 61 0 0
#> 43.1 12.10 1 61 0 1
#> 79.1 16.23 1 54 1 0
#> 170.1 19.54 1 43 0 1
#> 49.1 12.19 1 48 1 0
#> 85.2 16.44 1 36 0 0
#> 56 12.21 1 60 0 0
#> 181 16.46 1 45 0 1
#> 183.1 9.24 1 67 1 0
#> 39.1 15.59 1 37 0 1
#> 192.3 16.44 1 31 1 0
#> 195.4 11.76 1 NA 1 0
#> 63.1 22.77 1 31 1 0
#> 91.2 5.33 1 61 0 1
#> 88 18.37 1 47 0 0
#> 153 21.33 1 55 1 0
#> 66 22.13 1 53 0 0
#> 155 13.08 1 26 0 0
#> 188 16.16 1 46 0 1
#> 97 19.14 1 65 0 1
#> 18 15.21 1 49 1 0
#> 171 16.57 1 41 0 1
#> 14.1 12.89 1 21 0 0
#> 153.1 21.33 1 55 1 0
#> 188.1 16.16 1 46 0 1
#> 45 17.42 1 54 0 1
#> 113.1 22.86 1 34 0 0
#> 10 10.53 1 34 0 0
#> 89 11.44 1 NA 0 0
#> 185 24.00 0 44 1 0
#> 137 24.00 0 45 1 0
#> 143 24.00 0 51 0 0
#> 72 24.00 0 40 0 1
#> 193 24.00 0 45 0 1
#> 27 24.00 0 63 1 0
#> 7 24.00 0 37 1 0
#> 53 24.00 0 32 0 1
#> 35 24.00 0 51 0 0
#> 196 24.00 0 19 0 0
#> 31 24.00 0 36 0 1
#> 116 24.00 0 58 0 1
#> 31.1 24.00 0 36 0 1
#> 82 24.00 0 34 0 0
#> 115 24.00 0 NA 1 0
#> 174 24.00 0 49 1 0
#> 173 24.00 0 19 0 1
#> 119 24.00 0 17 0 0
#> 147 24.00 0 76 1 0
#> 11 24.00 0 42 0 1
#> 74 24.00 0 43 0 1
#> 178 24.00 0 52 1 0
#> 200 24.00 0 64 0 0
#> 119.1 24.00 0 17 0 0
#> 143.1 24.00 0 51 0 0
#> 7.1 24.00 0 37 1 0
#> 34 24.00 0 36 0 0
#> 71 24.00 0 51 0 0
#> 2 24.00 0 9 0 0
#> 156 24.00 0 50 1 0
#> 44 24.00 0 56 0 0
#> 173.1 24.00 0 19 0 1
#> 87 24.00 0 27 0 0
#> 122 24.00 0 66 0 0
#> 31.2 24.00 0 36 0 1
#> 198 24.00 0 66 0 1
#> 54 24.00 0 53 1 0
#> 122.1 24.00 0 66 0 0
#> 2.1 24.00 0 9 0 0
#> 35.1 24.00 0 51 0 0
#> 174.1 24.00 0 49 1 0
#> 38 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 122.2 24.00 0 66 0 0
#> 118 24.00 0 44 1 0
#> 48 24.00 0 31 1 0
#> 148 24.00 0 61 1 0
#> 144 24.00 0 28 0 1
#> 62 24.00 0 71 0 0
#> 22 24.00 0 52 1 0
#> 54.1 24.00 0 53 1 0
#> 48.1 24.00 0 31 1 0
#> 31.3 24.00 0 36 0 1
#> 122.3 24.00 0 66 0 0
#> 172 24.00 0 41 0 0
#> 115.1 24.00 0 NA 1 0
#> 102 24.00 0 49 0 0
#> 44.1 24.00 0 56 0 0
#> 121 24.00 0 57 1 0
#> 9 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 120.1 24.00 0 68 0 1
#> 193.1 24.00 0 45 0 1
#> 182 24.00 0 35 0 0
#> 1 24.00 0 23 1 0
#> 178.1 24.00 0 52 1 0
#> 64 24.00 0 43 0 0
#> 72.1 24.00 0 40 0 1
#> 193.2 24.00 0 45 0 1
#> 121.1 24.00 0 57 1 0
#> 72.2 24.00 0 40 0 1
#> 22.1 24.00 0 52 1 0
#> 142 24.00 0 53 0 0
#> 121.2 24.00 0 57 1 0
#> 72.3 24.00 0 40 0 1
#> 186 24.00 0 45 1 0
#> 80 24.00 0 41 0 0
#> 31.4 24.00 0 36 0 1
#> 83 24.00 0 6 0 0
#> 35.2 24.00 0 51 0 0
#> 135 24.00 0 58 1 0
#> 121.3 24.00 0 57 1 0
#> 87.1 24.00 0 27 0 0
#> 138 24.00 0 44 1 0
#> 176.1 24.00 0 43 0 1
#> 185.1 24.00 0 44 1 0
#> 3 24.00 0 31 1 0
#> 137.1 24.00 0 45 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.478 NA NA NA
#> 2 age, Cure model 0.0150 NA NA NA
#> 3 grade_ii, Cure model -0.165 NA NA NA
#> 4 grade_iii, Cure model 0.136 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00512 NA NA NA
#> 2 grade_ii, Survival model 0.419 NA NA NA
#> 3 grade_iii, Survival model 0.448 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.47837 0.01498 -0.16494 0.13622
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 258.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.4783725 0.0149831 -0.1649353 0.1362228
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.005119782 0.419262408 0.448404961
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.17125496 0.55707317 0.86451839 0.41796454 0.88933562 0.90764726
#> [7] 0.62235983 0.85185662 0.22213449 0.44764022 0.38528529 0.03073930
#> [13] 0.87698712 0.45756054 0.91972756 0.97785730 0.97785730 0.13084107
#> [19] 0.69134168 0.93160722 0.62235983 0.19042382 0.69134168 0.76720168
#> [25] 0.89551131 0.46742130 0.57384434 0.28121130 0.78059516 0.58212212
#> [31] 0.81980623 0.83911905 0.52261471 0.86451839 0.19042382 0.94331670
#> [37] 0.69134168 0.69134168 0.59031195 0.67644735 0.59031195 0.80686997
#> [43] 0.59031195 0.34956000 0.13084107 0.73968634 0.76720168 0.52261471
#> [49] 0.82628270 0.96653221 0.66121677 0.50480555 0.55707317 0.07001753
#> [55] 0.48657833 0.52261471 0.41796454 0.41796454 0.30955015 0.96077565
#> [61] 0.83270558 0.25301568 0.40717117 0.10511757 0.30955015 0.38528529
#> [67] 0.33645205 0.95498287 0.89551131 0.47703439 0.61433059 0.62235983
#> [73] 0.69134168 0.80686997 0.99446772 0.79378666 0.87698712 0.65347556
#> [79] 0.93160722 0.73968634 0.48657833 0.91972756 0.69134168 0.91369459
#> [85] 0.68393390 0.96653221 0.78059516 0.69134168 0.25301568 0.97785730
#> [91] 0.54838315 0.36214892 0.29548654 0.84549125 0.75356727 0.51380148
#> [97] 0.80035383 0.66887244 0.85185662 0.36214892 0.75356727 0.64570058
#> [103] 0.22213449 0.94915319 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 129 108 140 32 177 42 30 14 113 190 99 24 154
#> 23.41 18.29 12.68 20.90 12.53 12.43 17.43 12.89 22.86 20.81 21.19 23.89 12.63
#> 150 49 91 91.1 168 192 43 30.1 69 192.1 26 37 158
#> 20.33 12.19 5.33 5.33 23.72 16.44 12.10 17.43 23.23 16.44 15.77 12.52 20.14
#> 51 169 39 40 133 60 8 140.1 69.1 107 85 192.2 184
#> 18.23 22.41 15.59 18.00 14.65 13.15 18.43 12.68 23.23 11.18 16.44 16.44 17.77
#> 130 184.1 180 184.2 139 168.1 79 26.1 8.1 13 183 106 55
#> 16.47 17.77 14.82 17.77 21.49 23.72 16.23 15.77 18.43 14.34 9.24 16.67 19.34
#> 108.1 78 170 8.2 32.1 32.2 175 93 81 63 90 86 175.1
#> 18.29 23.88 19.54 18.43 20.90 20.90 21.91 10.33 14.06 22.77 20.94 23.81 21.91
#> 36 197 52 37.1 105 117 30.2 85.1 180.1 127 167 154.1 23
#> 21.19 21.60 10.42 12.52 19.75 17.46 17.43 16.44 14.82 3.53 15.55 12.63 16.92
#> 43.1 79.1 170.1 49.1 85.2 56 181 183.1 39.1 192.3 63.1 91.2 88
#> 12.10 16.23 19.54 12.19 16.44 12.21 16.46 9.24 15.59 16.44 22.77 5.33 18.37
#> 153 66 155 188 97 18 171 14.1 153.1 188.1 45 113.1 10
#> 21.33 22.13 13.08 16.16 19.14 15.21 16.57 12.89 21.33 16.16 17.42 22.86 10.53
#> 185 137 143 72 193 27 7 53 35 196 31 116 31.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82 174 173 119 147 11 74 178 200 119.1 143.1 7.1 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 2 156 44 173.1 87 122 31.2 198 54 122.1 2.1 35.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174.1 38 120 122.2 118 48 148 144 62 22 54.1 48.1 31.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122.3 172 102 44.1 121 9 176 120.1 193.1 182 1 178.1 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.1 193.2 121.1 72.2 22.1 142 121.2 72.3 186 80 31.4 83 35.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 121.3 87.1 138 176.1 185.1 3 137.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[17]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.02145881 0.35237067 0.31715646
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.332394490 -0.008908087 0.056377581
#> grade_iii, Cure model
#> 0.818139278
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 195 11.76 1 NA 1 0
#> 175 21.91 1 43 0 0
#> 127 3.53 1 62 0 1
#> 61 10.12 1 36 0 1
#> 5 16.43 1 51 0 1
#> 14 12.89 1 21 0 0
#> 150 20.33 1 48 0 0
#> 59 10.16 1 NA 1 0
#> 59.1 10.16 1 NA 1 0
#> 36 21.19 1 48 0 1
#> 30 17.43 1 78 0 0
#> 190 20.81 1 42 1 0
#> 127.1 3.53 1 62 0 1
#> 41 18.02 1 40 1 0
#> 89 11.44 1 NA 0 0
#> 29 15.45 1 68 1 0
#> 171 16.57 1 41 0 1
#> 110 17.56 1 65 0 1
#> 37 12.52 1 57 1 0
#> 25 6.32 1 34 1 0
#> 166 19.98 1 48 0 0
#> 129 23.41 1 53 1 0
#> 40 18.00 1 28 1 0
#> 14.1 12.89 1 21 0 0
#> 125 15.65 1 67 1 0
#> 158 20.14 1 74 1 0
#> 13 14.34 1 54 0 1
#> 105 19.75 1 60 0 0
#> 39 15.59 1 37 0 1
#> 55 19.34 1 69 0 1
#> 181 16.46 1 45 0 1
#> 154 12.63 1 20 1 0
#> 5.1 16.43 1 51 0 1
#> 32 20.90 1 37 1 0
#> 195.1 11.76 1 NA 1 0
#> 29.1 15.45 1 68 1 0
#> 61.1 10.12 1 36 0 1
#> 52 10.42 1 52 0 1
#> 15 22.68 1 48 0 0
#> 164 23.60 1 76 0 1
#> 168 23.72 1 70 0 0
#> 36.1 21.19 1 48 0 1
#> 99 21.19 1 38 0 1
#> 13.1 14.34 1 54 0 1
#> 110.1 17.56 1 65 0 1
#> 195.2 11.76 1 NA 1 0
#> 113 22.86 1 34 0 0
#> 92 22.92 1 47 0 1
#> 140 12.68 1 59 1 0
#> 68 20.62 1 44 0 0
#> 123 13.00 1 44 1 0
#> 154.1 12.63 1 20 1 0
#> 40.1 18.00 1 28 1 0
#> 5.2 16.43 1 51 0 1
#> 101 9.97 1 10 0 1
#> 107 11.18 1 54 1 0
#> 169 22.41 1 46 0 0
#> 155 13.08 1 26 0 0
#> 187 9.92 1 39 1 0
#> 96 14.54 1 33 0 1
#> 136 21.83 1 43 0 1
#> 199 19.81 1 NA 0 1
#> 190.1 20.81 1 42 1 0
#> 183 9.24 1 67 1 0
#> 42 12.43 1 49 0 1
#> 190.2 20.81 1 42 1 0
#> 127.2 3.53 1 62 0 1
#> 175.1 21.91 1 43 0 0
#> 25.1 6.32 1 34 1 0
#> 184 17.77 1 38 0 0
#> 170 19.54 1 43 0 1
#> 14.2 12.89 1 21 0 0
#> 60 13.15 1 38 1 0
#> 190.3 20.81 1 42 1 0
#> 136.1 21.83 1 43 0 1
#> 14.3 12.89 1 21 0 0
#> 134 17.81 1 47 1 0
#> 29.2 15.45 1 68 1 0
#> 37.1 12.52 1 57 1 0
#> 129.1 23.41 1 53 1 0
#> 23 16.92 1 61 0 0
#> 113.1 22.86 1 34 0 0
#> 171.1 16.57 1 41 0 1
#> 86 23.81 1 58 0 1
#> 117 17.46 1 26 0 1
#> 129.2 23.41 1 53 1 0
#> 13.2 14.34 1 54 0 1
#> 96.1 14.54 1 33 0 1
#> 76 19.22 1 54 0 1
#> 117.1 17.46 1 26 0 1
#> 81 14.06 1 34 0 0
#> 177 12.53 1 75 0 0
#> 101.1 9.97 1 10 0 1
#> 86.1 23.81 1 58 0 1
#> 32.1 20.90 1 37 1 0
#> 68.1 20.62 1 44 0 0
#> 68.2 20.62 1 44 0 0
#> 175.2 21.91 1 43 0 0
#> 155.1 13.08 1 26 0 0
#> 41.1 18.02 1 40 1 0
#> 130 16.47 1 53 0 1
#> 93 10.33 1 52 0 1
#> 6 15.64 1 39 0 0
#> 128 20.35 1 35 0 1
#> 179 18.63 1 42 0 0
#> 184.1 17.77 1 38 0 0
#> 140.1 12.68 1 59 1 0
#> 133 14.65 1 57 0 0
#> 68.3 20.62 1 44 0 0
#> 169.1 22.41 1 46 0 0
#> 45 17.42 1 54 0 1
#> 58 19.34 1 39 0 0
#> 122 24.00 0 66 0 0
#> 21 24.00 0 47 0 0
#> 178 24.00 0 52 1 0
#> 27 24.00 0 63 1 0
#> 31 24.00 0 36 0 1
#> 151 24.00 0 42 0 0
#> 109 24.00 0 48 0 0
#> 34 24.00 0 36 0 0
#> 47 24.00 0 38 0 1
#> 2 24.00 0 9 0 0
#> 46 24.00 0 71 0 0
#> 120 24.00 0 68 0 1
#> 151.1 24.00 0 42 0 0
#> 193 24.00 0 45 0 1
#> 54 24.00 0 53 1 0
#> 151.2 24.00 0 42 0 0
#> 74 24.00 0 43 0 1
#> 46.1 24.00 0 71 0 0
#> 84 24.00 0 39 0 1
#> 121 24.00 0 57 1 0
#> 109.1 24.00 0 48 0 0
#> 67 24.00 0 25 0 0
#> 109.2 24.00 0 48 0 0
#> 27.1 24.00 0 63 1 0
#> 120.1 24.00 0 68 0 1
#> 162 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 116 24.00 0 58 0 1
#> 75 24.00 0 21 1 0
#> 115 24.00 0 NA 1 0
#> 17 24.00 0 38 0 1
#> 135 24.00 0 58 1 0
#> 116.1 24.00 0 58 0 1
#> 178.1 24.00 0 52 1 0
#> 75.1 24.00 0 21 1 0
#> 138 24.00 0 44 1 0
#> 143 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 146 24.00 0 63 1 0
#> 80 24.00 0 41 0 0
#> 147 24.00 0 76 1 0
#> 186 24.00 0 45 1 0
#> 182 24.00 0 35 0 0
#> 7 24.00 0 37 1 0
#> 87 24.00 0 27 0 0
#> 146.1 24.00 0 63 1 0
#> 121.1 24.00 0 57 1 0
#> 160 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 120.2 24.00 0 68 0 1
#> 120.3 24.00 0 68 0 1
#> 178.2 24.00 0 52 1 0
#> 186.1 24.00 0 45 1 0
#> 95 24.00 0 68 0 1
#> 83 24.00 0 6 0 0
#> 119 24.00 0 17 0 0
#> 200 24.00 0 64 0 0
#> 75.2 24.00 0 21 1 0
#> 27.2 24.00 0 63 1 0
#> 53 24.00 0 32 0 1
#> 131 24.00 0 66 0 0
#> 186.2 24.00 0 45 1 0
#> 64 24.00 0 43 0 0
#> 47.1 24.00 0 38 0 1
#> 65 24.00 0 57 1 0
#> 22 24.00 0 52 1 0
#> 95.1 24.00 0 68 0 1
#> 75.3 24.00 0 21 1 0
#> 20 24.00 0 46 1 0
#> 74.1 24.00 0 43 0 1
#> 20.1 24.00 0 46 1 0
#> 135.1 24.00 0 58 1 0
#> 186.3 24.00 0 45 1 0
#> 9.1 24.00 0 31 1 0
#> 126 24.00 0 48 0 0
#> 109.3 24.00 0 48 0 0
#> 132 24.00 0 55 0 0
#> 7.1 24.00 0 37 1 0
#> 102 24.00 0 49 0 0
#> 11 24.00 0 42 0 1
#> 67.1 24.00 0 25 0 0
#> 200.1 24.00 0 64 0 0
#> 165 24.00 0 47 0 0
#> 193.1 24.00 0 45 0 1
#> 67.2 24.00 0 25 0 0
#> 12 24.00 0 63 0 0
#> 62 24.00 0 71 0 0
#> 165.1 24.00 0 47 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.332 NA NA NA
#> 2 age, Cure model -0.00891 NA NA NA
#> 3 grade_ii, Cure model 0.0564 NA NA NA
#> 4 grade_iii, Cure model 0.818 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0215 NA NA NA
#> 2 grade_ii, Survival model 0.352 NA NA NA
#> 3 grade_iii, Survival model 0.317 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.332394 -0.008908 0.056378 0.818139
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.5
#> Residual Deviance: 257.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.332394490 -0.008908087 0.056377581 0.818139278
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.02145881 0.35237067 0.31715646
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 1.203911e-02 9.441391e-01 8.017700e-01 3.033100e-01 5.615445e-01
#> [6] 8.216923e-02 2.509616e-02 2.324027e-01 4.232951e-02 9.441391e-01
#> [11] 1.409431e-01 3.717220e-01 2.616811e-01 1.966013e-01 7.000461e-01
#> [16] 9.079012e-01 9.357117e-02 9.479464e-04 1.561618e-01 5.615445e-01
#> [21] 3.362572e-01 8.773887e-02 4.482347e-01 9.964702e-02 3.597257e-01
#> [26] 1.125381e-01 2.925605e-01 6.523291e-01 3.033100e-01 3.490874e-02
#> [31] 3.717220e-01 8.017700e-01 7.669656e-01 6.562316e-03 4.346886e-04
#> [36] 1.621010e-04 2.509616e-02 2.509616e-02 4.482347e-01 1.966013e-01
#> [41] 4.036780e-03 2.939320e-03 6.209553e-01 5.801938e-02 5.466602e-01
#> [46] 6.523291e-01 1.561618e-01 3.033100e-01 8.369607e-01 7.498816e-01
#> [51] 8.206299e-03 5.176450e-01 8.719925e-01 4.219704e-01 1.922338e-02
#> [56] 4.232951e-02 8.898269e-01 7.330103e-01 4.232951e-02 9.441391e-01
#> [61] 1.203911e-02 9.079012e-01 1.798577e-01 1.060035e-01 5.615445e-01
#> [66] 5.032777e-01 4.232951e-02 1.922338e-02 5.615445e-01 1.717149e-01
#> [71] 3.717220e-01 7.000461e-01 9.479464e-04 2.516603e-01 4.036780e-03
#> [76] 2.616811e-01 1.293781e-05 2.143417e-01 9.479464e-04 4.482347e-01
#> [81] 4.219704e-01 1.261944e-01 2.143417e-01 4.890608e-01 6.838152e-01
#> [86] 8.369607e-01 1.293781e-05 3.490874e-02 5.801938e-02 5.801938e-02
#> [91] 1.203911e-02 5.176450e-01 1.409431e-01 2.819961e-01 7.842616e-01
#> [96] 3.478793e-01 7.683224e-02 1.334478e-01 1.798577e-01 6.209553e-01
#> [101] 4.088951e-01 5.801938e-02 8.206299e-03 2.419225e-01 1.125381e-01
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [191] 0.000000e+00 0.000000e+00
#>
#> $Time
#> 175 127 61 5 14 150 36 30 190 127.1 41 29 171
#> 21.91 3.53 10.12 16.43 12.89 20.33 21.19 17.43 20.81 3.53 18.02 15.45 16.57
#> 110 37 25 166 129 40 14.1 125 158 13 105 39 55
#> 17.56 12.52 6.32 19.98 23.41 18.00 12.89 15.65 20.14 14.34 19.75 15.59 19.34
#> 181 154 5.1 32 29.1 61.1 52 15 164 168 36.1 99 13.1
#> 16.46 12.63 16.43 20.90 15.45 10.12 10.42 22.68 23.60 23.72 21.19 21.19 14.34
#> 110.1 113 92 140 68 123 154.1 40.1 5.2 101 107 169 155
#> 17.56 22.86 22.92 12.68 20.62 13.00 12.63 18.00 16.43 9.97 11.18 22.41 13.08
#> 187 96 136 190.1 183 42 190.2 127.2 175.1 25.1 184 170 14.2
#> 9.92 14.54 21.83 20.81 9.24 12.43 20.81 3.53 21.91 6.32 17.77 19.54 12.89
#> 60 190.3 136.1 14.3 134 29.2 37.1 129.1 23 113.1 171.1 86 117
#> 13.15 20.81 21.83 12.89 17.81 15.45 12.52 23.41 16.92 22.86 16.57 23.81 17.46
#> 129.2 13.2 96.1 76 117.1 81 177 101.1 86.1 32.1 68.1 68.2 175.2
#> 23.41 14.34 14.54 19.22 17.46 14.06 12.53 9.97 23.81 20.90 20.62 20.62 21.91
#> 155.1 41.1 130 93 6 128 179 184.1 140.1 133 68.3 169.1 45
#> 13.08 18.02 16.47 10.33 15.64 20.35 18.63 17.77 12.68 14.65 20.62 22.41 17.42
#> 58 122 21 178 27 31 151 109 34 47 2 46 120
#> 19.34 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151.1 193 54 151.2 74 46.1 84 121 109.1 67 109.2 27.1 120.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 19 116 75 17 135 116.1 178.1 75.1 138 143 137 146
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 147 186 182 7 87 146.1 121.1 160 9 120.2 120.3 178.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186.1 95 83 119 200 75.2 27.2 53 131 186.2 64 47.1 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 95.1 75.3 20 74.1 20.1 135.1 186.3 9.1 126 109.3 132 7.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 11 67.1 200.1 165 193.1 67.2 12 62 165.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[18]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004815909 0.290529878 0.302666949
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.0762070660 -0.0006307045 -0.0065525427
#> grade_iii, Cure model
#> 0.8397699921
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 170 19.54 1 43 0 1
#> 154 12.63 1 20 1 0
#> 113 22.86 1 34 0 0
#> 194 22.40 1 38 0 1
#> 57 14.46 1 45 0 1
#> 136 21.83 1 43 0 1
#> 5 16.43 1 51 0 1
#> 134 17.81 1 47 1 0
#> 140 12.68 1 59 1 0
#> 93 10.33 1 52 0 1
#> 77 7.27 1 67 0 1
#> 23 16.92 1 61 0 0
#> 136.1 21.83 1 43 0 1
#> 177 12.53 1 75 0 0
#> 26 15.77 1 49 0 1
#> 13 14.34 1 54 0 1
#> 16 8.71 1 71 0 1
#> 92 22.92 1 47 0 1
#> 127 3.53 1 62 0 1
#> 6 15.64 1 39 0 0
#> 39 15.59 1 37 0 1
#> 68 20.62 1 44 0 0
#> 79 16.23 1 54 1 0
#> 171 16.57 1 41 0 1
#> 59 10.16 1 NA 1 0
#> 107 11.18 1 54 1 0
#> 79.1 16.23 1 54 1 0
#> 136.2 21.83 1 43 0 1
#> 113.1 22.86 1 34 0 0
#> 26.1 15.77 1 49 0 1
#> 81 14.06 1 34 0 0
#> 16.1 8.71 1 71 0 1
#> 23.1 16.92 1 61 0 0
#> 66 22.13 1 53 0 0
#> 14 12.89 1 21 0 0
#> 97 19.14 1 65 0 1
#> 108 18.29 1 39 0 1
#> 113.2 22.86 1 34 0 0
#> 123 13.00 1 44 1 0
#> 133 14.65 1 57 0 0
#> 63 22.77 1 31 1 0
#> 45 17.42 1 54 0 1
#> 81.1 14.06 1 34 0 0
#> 171.1 16.57 1 41 0 1
#> 107.1 11.18 1 54 1 0
#> 43 12.10 1 61 0 1
#> 85 16.44 1 36 0 0
#> 92.1 22.92 1 47 0 1
#> 192 16.44 1 31 1 0
#> 39.1 15.59 1 37 0 1
#> 136.3 21.83 1 43 0 1
#> 169 22.41 1 46 0 0
#> 63.1 22.77 1 31 1 0
#> 139 21.49 1 63 1 0
#> 199 19.81 1 NA 0 1
#> 50 10.02 1 NA 1 0
#> 85.1 16.44 1 36 0 0
#> 86 23.81 1 58 0 1
#> 55 19.34 1 69 0 1
#> 139.1 21.49 1 63 1 0
#> 170.1 19.54 1 43 0 1
#> 158 20.14 1 74 1 0
#> 97.1 19.14 1 65 0 1
#> 5.1 16.43 1 51 0 1
#> 78 23.88 1 43 0 0
#> 111 17.45 1 47 0 1
#> 58 19.34 1 39 0 0
#> 129 23.41 1 53 1 0
#> 16.2 8.71 1 71 0 1
#> 96 14.54 1 33 0 1
#> 78.1 23.88 1 43 0 0
#> 30 17.43 1 78 0 0
#> 59.1 10.16 1 NA 1 0
#> 42 12.43 1 49 0 1
#> 129.1 23.41 1 53 1 0
#> 189 10.51 1 NA 1 0
#> 111.1 17.45 1 47 0 1
#> 190 20.81 1 42 1 0
#> 43.1 12.10 1 61 0 1
#> 158.1 20.14 1 74 1 0
#> 127.1 3.53 1 62 0 1
#> 188 16.16 1 46 0 1
#> 134.1 17.81 1 47 1 0
#> 90 20.94 1 50 0 1
#> 159 10.55 1 50 0 1
#> 32 20.90 1 37 1 0
#> 164 23.60 1 76 0 1
#> 14.1 12.89 1 21 0 0
#> 195 11.76 1 NA 1 0
#> 60 13.15 1 38 1 0
#> 154.1 12.63 1 20 1 0
#> 66.1 22.13 1 53 0 0
#> 92.2 22.92 1 47 0 1
#> 195.1 11.76 1 NA 1 0
#> 41 18.02 1 40 1 0
#> 39.2 15.59 1 37 0 1
#> 164.1 23.60 1 76 0 1
#> 177.1 12.53 1 75 0 0
#> 130 16.47 1 53 0 1
#> 30.1 17.43 1 78 0 0
#> 36 21.19 1 48 0 1
#> 136.4 21.83 1 43 0 1
#> 101 9.97 1 10 0 1
#> 88 18.37 1 47 0 0
#> 194.1 22.40 1 38 0 1
#> 167 15.55 1 56 1 0
#> 26.2 15.77 1 49 0 1
#> 101.1 9.97 1 10 0 1
#> 4 17.64 1 NA 0 1
#> 184 17.77 1 38 0 0
#> 70 7.38 1 30 1 0
#> 105 19.75 1 60 0 0
#> 152 24.00 0 36 0 1
#> 11 24.00 0 42 0 1
#> 87 24.00 0 27 0 0
#> 122 24.00 0 66 0 0
#> 178 24.00 0 52 1 0
#> 2 24.00 0 9 0 0
#> 147 24.00 0 76 1 0
#> 143 24.00 0 51 0 0
#> 116 24.00 0 58 0 1
#> 131 24.00 0 66 0 0
#> 95 24.00 0 68 0 1
#> 104 24.00 0 50 1 0
#> 146 24.00 0 63 1 0
#> 33 24.00 0 53 0 0
#> 64 24.00 0 43 0 0
#> 196 24.00 0 19 0 0
#> 196.1 24.00 0 19 0 0
#> 104.1 24.00 0 50 1 0
#> 53 24.00 0 32 0 1
#> 73 24.00 0 NA 0 1
#> 33.1 24.00 0 53 0 0
#> 126 24.00 0 48 0 0
#> 185 24.00 0 44 1 0
#> 12 24.00 0 63 0 0
#> 21 24.00 0 47 0 0
#> 22 24.00 0 52 1 0
#> 80 24.00 0 41 0 0
#> 73.1 24.00 0 NA 0 1
#> 120 24.00 0 68 0 1
#> 115 24.00 0 NA 1 0
#> 95.1 24.00 0 68 0 1
#> 132 24.00 0 55 0 0
#> 176 24.00 0 43 0 1
#> 31 24.00 0 36 0 1
#> 71 24.00 0 51 0 0
#> 73.2 24.00 0 NA 0 1
#> 44 24.00 0 56 0 0
#> 174 24.00 0 49 1 0
#> 54 24.00 0 53 1 0
#> 95.2 24.00 0 68 0 1
#> 137 24.00 0 45 1 0
#> 34 24.00 0 36 0 0
#> 35 24.00 0 51 0 0
#> 119 24.00 0 17 0 0
#> 94 24.00 0 51 0 1
#> 74 24.00 0 43 0 1
#> 72 24.00 0 40 0 1
#> 12.1 24.00 0 63 0 0
#> 115.1 24.00 0 NA 1 0
#> 84 24.00 0 39 0 1
#> 1 24.00 0 23 1 0
#> 28 24.00 0 67 1 0
#> 138 24.00 0 44 1 0
#> 33.2 24.00 0 53 0 0
#> 65 24.00 0 57 1 0
#> 116.1 24.00 0 58 0 1
#> 116.2 24.00 0 58 0 1
#> 198 24.00 0 66 0 1
#> 148 24.00 0 61 1 0
#> 163 24.00 0 66 0 0
#> 147.1 24.00 0 76 1 0
#> 165 24.00 0 47 0 0
#> 12.2 24.00 0 63 0 0
#> 12.3 24.00 0 63 0 0
#> 147.2 24.00 0 76 1 0
#> 80.1 24.00 0 41 0 0
#> 47 24.00 0 38 0 1
#> 74.1 24.00 0 43 0 1
#> 118 24.00 0 44 1 0
#> 95.3 24.00 0 68 0 1
#> 72.1 24.00 0 40 0 1
#> 102 24.00 0 49 0 0
#> 11.1 24.00 0 42 0 1
#> 1.1 24.00 0 23 1 0
#> 2.1 24.00 0 9 0 0
#> 20 24.00 0 46 1 0
#> 193 24.00 0 45 0 1
#> 48 24.00 0 31 1 0
#> 152.1 24.00 0 36 0 1
#> 48.1 24.00 0 31 1 0
#> 141 24.00 0 44 1 0
#> 138.1 24.00 0 44 1 0
#> 186 24.00 0 45 1 0
#> 135 24.00 0 58 1 0
#> 156 24.00 0 50 1 0
#> 84.1 24.00 0 39 0 1
#> 20.1 24.00 0 46 1 0
#> 34.1 24.00 0 36 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.0762 NA NA NA
#> 2 age, Cure model -0.000631 NA NA NA
#> 3 grade_ii, Cure model -0.00655 NA NA NA
#> 4 grade_iii, Cure model 0.840 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00482 NA NA NA
#> 2 grade_ii, Survival model 0.291 NA NA NA
#> 3 grade_iii, Survival model 0.303 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.0762071 -0.0006307 -0.0065525 0.8397700
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 256.9
#> Residual Deviance: 249.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.0762070660 -0.0006307045 -0.0065525427 0.8397699921
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004815909 0.290529878 0.302666949
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.338035199 0.808393494 0.102716149 0.159967626 0.721752207 0.198614818
#> [7] 0.577663623 0.423913340 0.798730554 0.904527332 0.971342776 0.500413980
#> [13] 0.198614818 0.827506537 0.625991871 0.731387330 0.933255021 0.075715543
#> [19] 0.980926900 0.654590450 0.664290161 0.299977474 0.596980964 0.519814610
#> [25] 0.875656147 0.596980964 0.198614818 0.102716149 0.625991871 0.741016933
#> [31] 0.933255021 0.500413980 0.179055581 0.779520098 0.375950900 0.404643782
#> [37] 0.102716149 0.769877962 0.702438608 0.130873215 0.490714492 0.741016933
#> [43] 0.519814610 0.875656147 0.856425982 0.548875273 0.075715543 0.548875273
#> [49] 0.664290161 0.198614818 0.149965568 0.130873215 0.242993553 0.548875273
#> [55] 0.024646765 0.356942490 0.242993553 0.338035199 0.309522242 0.375950900
#> [61] 0.577663623 0.007203447 0.452509677 0.356942490 0.055918140 0.933255021
#> [67] 0.712105529 0.007203447 0.471490874 0.846754367 0.055918140 0.452509677
#> [73] 0.290490368 0.856425982 0.309522242 0.980926900 0.616279040 0.423913340
#> [79] 0.271420429 0.894873273 0.280974617 0.035947959 0.779520098 0.760225939
#> [85] 0.808393494 0.179055581 0.075715543 0.414290077 0.664290161 0.035947959
#> [91] 0.827506537 0.539135328 0.471490874 0.261844765 0.198614818 0.914175869
#> [97] 0.394969431 0.159967626 0.692803520 0.625991871 0.914175869 0.442885111
#> [103] 0.961760526 0.328390791 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 170 154 113 194 57 136 5 134 140 93 77 23 136.1
#> 19.54 12.63 22.86 22.40 14.46 21.83 16.43 17.81 12.68 10.33 7.27 16.92 21.83
#> 177 26 13 16 92 127 6 39 68 79 171 107 79.1
#> 12.53 15.77 14.34 8.71 22.92 3.53 15.64 15.59 20.62 16.23 16.57 11.18 16.23
#> 136.2 113.1 26.1 81 16.1 23.1 66 14 97 108 113.2 123 133
#> 21.83 22.86 15.77 14.06 8.71 16.92 22.13 12.89 19.14 18.29 22.86 13.00 14.65
#> 63 45 81.1 171.1 107.1 43 85 92.1 192 39.1 136.3 169 63.1
#> 22.77 17.42 14.06 16.57 11.18 12.10 16.44 22.92 16.44 15.59 21.83 22.41 22.77
#> 139 85.1 86 55 139.1 170.1 158 97.1 5.1 78 111 58 129
#> 21.49 16.44 23.81 19.34 21.49 19.54 20.14 19.14 16.43 23.88 17.45 19.34 23.41
#> 16.2 96 78.1 30 42 129.1 111.1 190 43.1 158.1 127.1 188 134.1
#> 8.71 14.54 23.88 17.43 12.43 23.41 17.45 20.81 12.10 20.14 3.53 16.16 17.81
#> 90 159 32 164 14.1 60 154.1 66.1 92.2 41 39.2 164.1 177.1
#> 20.94 10.55 20.90 23.60 12.89 13.15 12.63 22.13 22.92 18.02 15.59 23.60 12.53
#> 130 30.1 36 136.4 101 88 194.1 167 26.2 101.1 184 70 105
#> 16.47 17.43 21.19 21.83 9.97 18.37 22.40 15.55 15.77 9.97 17.77 7.38 19.75
#> 152 11 87 122 178 2 147 143 116 131 95 104 146
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 64 196 196.1 104.1 53 33.1 126 185 12 21 22 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 95.1 132 176 31 71 44 174 54 95.2 137 34 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119 94 74 72 12.1 84 1 28 138 33.2 65 116.1 116.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 148 163 147.1 165 12.2 12.3 147.2 80.1 47 74.1 118 95.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.1 102 11.1 1.1 2.1 20 193 48 152.1 48.1 141 138.1 186
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 156 84.1 20.1 34.1
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[19]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002847261 0.322415332 0.410306207
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.03647856 0.02220617 -0.09237595
#> grade_iii, Cure model
#> 0.56041518
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 58 19.34 1 39 0 0
#> 8 18.43 1 32 0 0
#> 189 10.51 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 106 16.67 1 49 1 0
#> 155 13.08 1 26 0 0
#> 129 23.41 1 53 1 0
#> 76 19.22 1 54 0 1
#> 49 12.19 1 48 1 0
#> 183 9.24 1 67 1 0
#> 199 19.81 1 NA 0 1
#> 37 12.52 1 57 1 0
#> 29 15.45 1 68 1 0
#> 189.1 10.51 1 NA 1 0
#> 88 18.37 1 47 0 0
#> 139 21.49 1 63 1 0
#> 10 10.53 1 34 0 0
#> 39 15.59 1 37 0 1
#> 139.1 21.49 1 63 1 0
#> 91 5.33 1 61 0 1
#> 58.1 19.34 1 39 0 0
#> 169 22.41 1 46 0 0
#> 77 7.27 1 67 0 1
#> 58.2 19.34 1 39 0 0
#> 127 3.53 1 62 0 1
#> 63 22.77 1 31 1 0
#> 24 23.89 1 38 0 0
#> 42 12.43 1 49 0 1
#> 166 19.98 1 48 0 0
#> 39.1 15.59 1 37 0 1
#> 30 17.43 1 78 0 0
#> 169.1 22.41 1 46 0 0
#> 23 16.92 1 61 0 0
#> 129.1 23.41 1 53 1 0
#> 195 11.76 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 158 20.14 1 74 1 0
#> 55 19.34 1 69 0 1
#> 187 9.92 1 39 1 0
#> 85 16.44 1 36 0 0
#> 158.1 20.14 1 74 1 0
#> 45 17.42 1 54 0 1
#> 157 15.10 1 47 0 0
#> 16 8.71 1 71 0 1
#> 168 23.72 1 70 0 0
#> 108 18.29 1 39 0 1
#> 55.1 19.34 1 69 0 1
#> 114 13.68 1 NA 0 0
#> 63.1 22.77 1 31 1 0
#> 117 17.46 1 26 0 1
#> 56 12.21 1 60 0 0
#> 107 11.18 1 54 1 0
#> 61 10.12 1 36 0 1
#> 192 16.44 1 31 1 0
#> 63.2 22.77 1 31 1 0
#> 111 17.45 1 47 0 1
#> 189.2 10.51 1 NA 1 0
#> 110 17.56 1 65 0 1
#> 92 22.92 1 47 0 1
#> 41 18.02 1 40 1 0
#> 136 21.83 1 43 0 1
#> 192.1 16.44 1 31 1 0
#> 114.1 13.68 1 NA 0 0
#> 158.2 20.14 1 74 1 0
#> 177.1 12.53 1 75 0 0
#> 30.1 17.43 1 78 0 0
#> 30.2 17.43 1 78 0 0
#> 167 15.55 1 56 1 0
#> 150 20.33 1 48 0 0
#> 149 8.37 1 33 1 0
#> 192.2 16.44 1 31 1 0
#> 49.1 12.19 1 48 1 0
#> 25 6.32 1 34 1 0
#> 5 16.43 1 51 0 1
#> 192.3 16.44 1 31 1 0
#> 51 18.23 1 83 0 1
#> 164 23.60 1 76 0 1
#> 58.3 19.34 1 39 0 0
#> 153 21.33 1 55 1 0
#> 61.1 10.12 1 36 0 1
#> 100 16.07 1 60 0 0
#> 155.1 13.08 1 26 0 0
#> 97 19.14 1 65 0 1
#> 199.1 19.81 1 NA 0 1
#> 153.1 21.33 1 55 1 0
#> 130 16.47 1 53 0 1
#> 13 14.34 1 54 0 1
#> 51.1 18.23 1 83 0 1
#> 197 21.60 1 69 1 0
#> 30.3 17.43 1 78 0 0
#> 155.2 13.08 1 26 0 0
#> 154 12.63 1 20 1 0
#> 107.1 11.18 1 54 1 0
#> 168.1 23.72 1 70 0 0
#> 199.2 19.81 1 NA 0 1
#> 183.1 9.24 1 67 1 0
#> 166.1 19.98 1 48 0 0
#> 129.2 23.41 1 53 1 0
#> 183.2 9.24 1 67 1 0
#> 190 20.81 1 42 1 0
#> 42.1 12.43 1 49 0 1
#> 169.2 22.41 1 46 0 0
#> 124 9.73 1 NA 1 0
#> 125 15.65 1 67 1 0
#> 16.1 8.71 1 71 0 1
#> 114.2 13.68 1 NA 0 0
#> 149.1 8.37 1 33 1 0
#> 170 19.54 1 43 0 1
#> 136.1 21.83 1 43 0 1
#> 86 23.81 1 58 0 1
#> 76.1 19.22 1 54 0 1
#> 123 13.00 1 44 1 0
#> 121 24.00 0 57 1 0
#> 11 24.00 0 42 0 1
#> 174 24.00 0 49 1 0
#> 27 24.00 0 63 1 0
#> 178 24.00 0 52 1 0
#> 27.1 24.00 0 63 1 0
#> 12 24.00 0 63 0 0
#> 103 24.00 0 56 1 0
#> 54 24.00 0 53 1 0
#> 12.1 24.00 0 63 0 0
#> 72 24.00 0 40 0 1
#> 165 24.00 0 47 0 0
#> 148 24.00 0 61 1 0
#> 98 24.00 0 34 1 0
#> 72.1 24.00 0 40 0 1
#> 131 24.00 0 66 0 0
#> 44 24.00 0 56 0 0
#> 3 24.00 0 31 1 0
#> 173 24.00 0 19 0 1
#> 148.1 24.00 0 61 1 0
#> 126 24.00 0 48 0 0
#> 176 24.00 0 43 0 1
#> 112 24.00 0 61 0 0
#> 3.1 24.00 0 31 1 0
#> 44.1 24.00 0 56 0 0
#> 54.1 24.00 0 53 1 0
#> 67 24.00 0 25 0 0
#> 131.1 24.00 0 66 0 0
#> 54.2 24.00 0 53 1 0
#> 118 24.00 0 44 1 0
#> 104 24.00 0 50 1 0
#> 11.1 24.00 0 42 0 1
#> 165.1 24.00 0 47 0 0
#> 121.1 24.00 0 57 1 0
#> 95 24.00 0 68 0 1
#> 148.2 24.00 0 61 1 0
#> 135 24.00 0 58 1 0
#> 2 24.00 0 9 0 0
#> 119 24.00 0 17 0 0
#> 160 24.00 0 31 1 0
#> 121.2 24.00 0 57 1 0
#> 84 24.00 0 39 0 1
#> 119.1 24.00 0 17 0 0
#> 80 24.00 0 41 0 0
#> 186 24.00 0 45 1 0
#> 116 24.00 0 58 0 1
#> 138 24.00 0 44 1 0
#> 94 24.00 0 51 0 1
#> 53 24.00 0 32 0 1
#> 84.1 24.00 0 39 0 1
#> 182 24.00 0 35 0 0
#> 22 24.00 0 52 1 0
#> 146 24.00 0 63 1 0
#> 146.1 24.00 0 63 1 0
#> 34 24.00 0 36 0 0
#> 135.1 24.00 0 58 1 0
#> 84.2 24.00 0 39 0 1
#> 135.2 24.00 0 58 1 0
#> 46 24.00 0 71 0 0
#> 21 24.00 0 47 0 0
#> 131.2 24.00 0 66 0 0
#> 121.3 24.00 0 57 1 0
#> 73 24.00 0 NA 0 1
#> 22.1 24.00 0 52 1 0
#> 19 24.00 0 57 0 1
#> 80.1 24.00 0 41 0 0
#> 64 24.00 0 43 0 0
#> 7 24.00 0 37 1 0
#> 35 24.00 0 51 0 0
#> 98.1 24.00 0 34 1 0
#> 11.2 24.00 0 42 0 1
#> 109 24.00 0 48 0 0
#> 64.1 24.00 0 43 0 0
#> 115 24.00 0 NA 1 0
#> 98.2 24.00 0 34 1 0
#> 135.3 24.00 0 58 1 0
#> 38 24.00 0 31 1 0
#> 196 24.00 0 19 0 0
#> 118.1 24.00 0 44 1 0
#> 165.2 24.00 0 47 0 0
#> 48 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 135.4 24.00 0 58 1 0
#> 196.1 24.00 0 19 0 0
#> 46.1 24.00 0 71 0 0
#> 11.3 24.00 0 42 0 1
#> 7.1 24.00 0 37 1 0
#> 161 24.00 0 45 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.04 NA NA NA
#> 2 age, Cure model 0.0222 NA NA NA
#> 3 grade_ii, Cure model -0.0924 NA NA NA
#> 4 grade_iii, Cure model 0.560 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00285 NA NA NA
#> 2 grade_ii, Survival model 0.322 NA NA NA
#> 3 grade_iii, Survival model 0.410 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.03648 0.02221 -0.09238 0.56042
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258
#> Residual Deviance: 249.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.03647856 0.02220617 -0.09237595 0.56041518
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002847261 0.322415332 0.410306207
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.352972726 0.439095773 0.020554866 0.583106228 0.730928981 0.090538250
#> [7] 0.409681154 0.831179114 0.903094256 0.794792326 0.703328670 0.448957795
#> [13] 0.231186481 0.867217516 0.675753722 0.231186481 0.982471228 0.352972726
#> [19] 0.167468405 0.964859954 0.352972726 0.991245818 0.136331396 0.006745204
#> [25] 0.803959525 0.322576254 0.675753722 0.526348834 0.167468405 0.573494519
#> [31] 0.090538250 0.776527294 0.292946861 0.352972726 0.894135349 0.602220635
#> [37] 0.292946861 0.563908429 0.712530265 0.929595420 0.049948300 0.458847032
#> [43] 0.352972726 0.136331396 0.507266928 0.822061760 0.849233428 0.876265371
#> [49] 0.602220635 0.136331396 0.516835925 0.497625236 0.124266814 0.487936129
#> [55] 0.199348564 0.602220635 0.292946861 0.776527294 0.526348834 0.526348834
#> [61] 0.694110499 0.282590050 0.947269799 0.602220635 0.831179114 0.973675668
#> [67] 0.647739976 0.602220635 0.468662480 0.076450474 0.352972726 0.251884603
#> [73] 0.876265371 0.657070130 0.730928981 0.429253012 0.251884603 0.592686250
#> [79] 0.721746769 0.468662480 0.220444120 0.526348834 0.730928981 0.767382052
#> [85] 0.849233428 0.049948300 0.903094256 0.322576254 0.090538250 0.903094256
#> [91] 0.272281536 0.803959525 0.167468405 0.666421138 0.929595420 0.947269799
#> [97] 0.342805748 0.199348564 0.036024397 0.409681154 0.758203555 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 58 8 78 106 155 129 76 49 183 37 29 88 139
#> 19.34 18.43 23.88 16.67 13.08 23.41 19.22 12.19 9.24 12.52 15.45 18.37 21.49
#> 10 39 139.1 91 58.1 169 77 58.2 127 63 24 42 166
#> 10.53 15.59 21.49 5.33 19.34 22.41 7.27 19.34 3.53 22.77 23.89 12.43 19.98
#> 39.1 30 169.1 23 129.1 177 158 55 187 85 158.1 45 157
#> 15.59 17.43 22.41 16.92 23.41 12.53 20.14 19.34 9.92 16.44 20.14 17.42 15.10
#> 16 168 108 55.1 63.1 117 56 107 61 192 63.2 111 110
#> 8.71 23.72 18.29 19.34 22.77 17.46 12.21 11.18 10.12 16.44 22.77 17.45 17.56
#> 92 41 136 192.1 158.2 177.1 30.1 30.2 167 150 149 192.2 49.1
#> 22.92 18.02 21.83 16.44 20.14 12.53 17.43 17.43 15.55 20.33 8.37 16.44 12.19
#> 25 5 192.3 51 164 58.3 153 61.1 100 155.1 97 153.1 130
#> 6.32 16.43 16.44 18.23 23.60 19.34 21.33 10.12 16.07 13.08 19.14 21.33 16.47
#> 13 51.1 197 30.3 155.2 154 107.1 168.1 183.1 166.1 129.2 183.2 190
#> 14.34 18.23 21.60 17.43 13.08 12.63 11.18 23.72 9.24 19.98 23.41 9.24 20.81
#> 42.1 169.2 125 16.1 149.1 170 136.1 86 76.1 123 121 11 174
#> 12.43 22.41 15.65 8.71 8.37 19.54 21.83 23.81 19.22 13.00 24.00 24.00 24.00
#> 27 178 27.1 12 103 54 12.1 72 165 148 98 72.1 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 3 173 148.1 126 176 112 3.1 44.1 54.1 67 131.1 54.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 104 11.1 165.1 121.1 95 148.2 135 2 119 160 121.2 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119.1 80 186 116 138 94 53 84.1 182 22 146 146.1 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135.1 84.2 135.2 46 21 131.2 121.3 22.1 19 80.1 64 7 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.1 11.2 109 64.1 98.2 135.3 38 196 118.1 165.2 48 152 135.4
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196.1 46.1 11.3 7.1 161
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[20]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002632963 0.379044155 0.029999809
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.36769764 0.02387603 0.43339501
#> grade_iii, Cure model
#> 0.74061013
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 184 17.77 1 38 0 0
#> 157 15.10 1 47 0 0
#> 88 18.37 1 47 0 0
#> 110 17.56 1 65 0 1
#> 32 20.90 1 37 1 0
#> 86 23.81 1 58 0 1
#> 168 23.72 1 70 0 0
#> 157.1 15.10 1 47 0 0
#> 57 14.46 1 45 0 1
#> 76 19.22 1 54 0 1
#> 106 16.67 1 49 1 0
#> 97 19.14 1 65 0 1
#> 81 14.06 1 34 0 0
#> 91 5.33 1 61 0 1
#> 68 20.62 1 44 0 0
#> 18 15.21 1 49 1 0
#> 187 9.92 1 39 1 0
#> 139 21.49 1 63 1 0
#> 32.1 20.90 1 37 1 0
#> 171 16.57 1 41 0 1
#> 88.1 18.37 1 47 0 0
#> 32.2 20.90 1 37 1 0
#> 153 21.33 1 55 1 0
#> 81.1 14.06 1 34 0 0
#> 8 18.43 1 32 0 0
#> 52 10.42 1 52 0 1
#> 69 23.23 1 25 0 1
#> 111 17.45 1 47 0 1
#> 91.1 5.33 1 61 0 1
#> 139.1 21.49 1 63 1 0
#> 192 16.44 1 31 1 0
#> 188 16.16 1 46 0 1
#> 110.1 17.56 1 65 0 1
#> 30 17.43 1 78 0 0
#> 61 10.12 1 36 0 1
#> 123 13.00 1 44 1 0
#> 170 19.54 1 43 0 1
#> 56 12.21 1 60 0 0
#> 114 13.68 1 NA 0 0
#> 192.1 16.44 1 31 1 0
#> 167 15.55 1 56 1 0
#> 113 22.86 1 34 0 0
#> 89 11.44 1 NA 0 0
#> 52.1 10.42 1 52 0 1
#> 79 16.23 1 54 1 0
#> 18.1 15.21 1 49 1 0
#> 167.1 15.55 1 56 1 0
#> 192.2 16.44 1 31 1 0
#> 15 22.68 1 48 0 0
#> 168.1 23.72 1 70 0 0
#> 4 17.64 1 NA 0 1
#> 68.1 20.62 1 44 0 0
#> 164 23.60 1 76 0 1
#> 25 6.32 1 34 1 0
#> 36 21.19 1 48 0 1
#> 190 20.81 1 42 1 0
#> 88.2 18.37 1 47 0 0
#> 158 20.14 1 74 1 0
#> 128 20.35 1 35 0 1
#> 129 23.41 1 53 1 0
#> 194 22.40 1 38 0 1
#> 32.3 20.90 1 37 1 0
#> 4.1 17.64 1 NA 0 1
#> 79.1 16.23 1 54 1 0
#> 140 12.68 1 59 1 0
#> 51 18.23 1 83 0 1
#> 177 12.53 1 75 0 0
#> 91.2 5.33 1 61 0 1
#> 199 19.81 1 NA 0 1
#> 199.1 19.81 1 NA 0 1
#> 177.1 12.53 1 75 0 0
#> 169 22.41 1 46 0 0
#> 113.1 22.86 1 34 0 0
#> 37 12.52 1 57 1 0
#> 40 18.00 1 28 1 0
#> 60 13.15 1 38 1 0
#> 93 10.33 1 52 0 1
#> 49 12.19 1 48 1 0
#> 100 16.07 1 60 0 0
#> 52.2 10.42 1 52 0 1
#> 88.3 18.37 1 47 0 0
#> 59 10.16 1 NA 1 0
#> 90 20.94 1 50 0 1
#> 30.1 17.43 1 78 0 0
#> 123.1 13.00 1 44 1 0
#> 154 12.63 1 20 1 0
#> 5 16.43 1 51 0 1
#> 114.1 13.68 1 NA 0 0
#> 158.1 20.14 1 74 1 0
#> 177.2 12.53 1 75 0 0
#> 4.2 17.64 1 NA 0 1
#> 136 21.83 1 43 0 1
#> 125 15.65 1 67 1 0
#> 4.3 17.64 1 NA 0 1
#> 189 10.51 1 NA 1 0
#> 195 11.76 1 NA 1 0
#> 179 18.63 1 42 0 0
#> 170.1 19.54 1 43 0 1
#> 107 11.18 1 54 1 0
#> 8.1 18.43 1 32 0 0
#> 49.1 12.19 1 48 1 0
#> 183 9.24 1 67 1 0
#> 136.1 21.83 1 43 0 1
#> 184.1 17.77 1 38 0 0
#> 23 16.92 1 61 0 0
#> 158.2 20.14 1 74 1 0
#> 194.1 22.40 1 38 0 1
#> 85 16.44 1 36 0 0
#> 197 21.60 1 69 1 0
#> 29 15.45 1 68 1 0
#> 52.3 10.42 1 52 0 1
#> 76.1 19.22 1 54 0 1
#> 122 24.00 0 66 0 0
#> 38 24.00 0 31 1 0
#> 54 24.00 0 53 1 0
#> 131 24.00 0 66 0 0
#> 27 24.00 0 63 1 0
#> 21 24.00 0 47 0 0
#> 144 24.00 0 28 0 1
#> 3 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 47 24.00 0 38 0 1
#> 173 24.00 0 19 0 1
#> 34 24.00 0 36 0 0
#> 27.1 24.00 0 63 1 0
#> 143 24.00 0 51 0 0
#> 119 24.00 0 17 0 0
#> 200 24.00 0 64 0 0
#> 146 24.00 0 63 1 0
#> 1 24.00 0 23 1 0
#> 38.1 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 21.1 24.00 0 47 0 0
#> 112 24.00 0 61 0 0
#> 35 24.00 0 51 0 0
#> 73 24.00 0 NA 0 1
#> 34.1 24.00 0 36 0 0
#> 193 24.00 0 45 0 1
#> 185 24.00 0 44 1 0
#> 156 24.00 0 50 1 0
#> 19 24.00 0 57 0 1
#> 94 24.00 0 51 0 1
#> 196 24.00 0 19 0 0
#> 121 24.00 0 57 1 0
#> 34.2 24.00 0 36 0 0
#> 174 24.00 0 49 1 0
#> 196.1 24.00 0 19 0 0
#> 38.2 24.00 0 31 1 0
#> 44 24.00 0 56 0 0
#> 135 24.00 0 58 1 0
#> 141 24.00 0 44 1 0
#> 21.2 24.00 0 47 0 0
#> 65 24.00 0 57 1 0
#> 9 24.00 0 31 1 0
#> 163 24.00 0 66 0 0
#> 160 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 3.1 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 72.1 24.00 0 40 0 1
#> 71 24.00 0 51 0 0
#> 9.1 24.00 0 31 1 0
#> 71.1 24.00 0 51 0 0
#> 121.1 24.00 0 57 1 0
#> 35.1 24.00 0 51 0 0
#> 174.1 24.00 0 49 1 0
#> 122.1 24.00 0 66 0 0
#> 132 24.00 0 55 0 0
#> 165 24.00 0 47 0 0
#> 146.1 24.00 0 63 1 0
#> 161 24.00 0 45 0 0
#> 65.1 24.00 0 57 1 0
#> 176 24.00 0 43 0 1
#> 64 24.00 0 43 0 0
#> 147 24.00 0 76 1 0
#> 72.2 24.00 0 40 0 1
#> 176.1 24.00 0 43 0 1
#> 138 24.00 0 44 1 0
#> 186 24.00 0 45 1 0
#> 198 24.00 0 66 0 1
#> 2 24.00 0 9 0 0
#> 87 24.00 0 27 0 0
#> 196.2 24.00 0 19 0 0
#> 198.1 24.00 0 66 0 1
#> 162 24.00 0 51 0 0
#> 31 24.00 0 36 0 1
#> 9.2 24.00 0 31 1 0
#> 131.1 24.00 0 66 0 0
#> 143.1 24.00 0 51 0 0
#> 144.1 24.00 0 28 0 1
#> 67 24.00 0 25 0 0
#> 131.2 24.00 0 66 0 0
#> 11 24.00 0 42 0 1
#> 46 24.00 0 71 0 0
#> 196.3 24.00 0 19 0 0
#> 116 24.00 0 58 0 1
#> 132.1 24.00 0 55 0 0
#> 31.1 24.00 0 36 0 1
#> 156.1 24.00 0 50 1 0
#> 95 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.37 NA NA NA
#> 2 age, Cure model 0.0239 NA NA NA
#> 3 grade_ii, Cure model 0.433 NA NA NA
#> 4 grade_iii, Cure model 0.741 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00263 NA NA NA
#> 2 grade_ii, Survival model 0.379 NA NA NA
#> 3 grade_iii, Survival model 0.0300 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.36770 0.02388 0.43340 0.74061
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258.3
#> Residual Deviance: 249.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.36769764 0.02387603 0.43339501 0.74061013
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002632963 0.379044155 0.029999809
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.462997105 0.711716781 0.403833053 0.482953966 0.218942899 0.004970795
#> [7] 0.015396476 0.711716781 0.731165923 0.344620752 0.543680910 0.364162246
#> [13] 0.740967153 0.971524113 0.266890967 0.692329337 0.942783695 0.165436832
#> [19] 0.218942899 0.553880169 0.403833053 0.218942899 0.186590759 0.740967153
#> [25] 0.384072141 0.885633597 0.056174417 0.503020079 0.971524113 0.165436832
#> [31] 0.564093536 0.632982372 0.482953966 0.513173554 0.933147180 0.770265069
#> [37] 0.325196402 0.847253825 0.564093536 0.662884999 0.067099729 0.885633597
#> [43] 0.613238352 0.692329337 0.662884999 0.564093536 0.087744947 0.015396476
#> [49] 0.266890967 0.033754220 0.961972511 0.197320664 0.256935630 0.403833053
#> [55] 0.296633975 0.286588628 0.045329779 0.110256532 0.218942899 0.613238352
#> [61] 0.789556634 0.442823740 0.808862876 0.971524113 0.808862876 0.098927086
#> [67] 0.067099729 0.837593920 0.452950517 0.760483912 0.923516905 0.856929853
#> [73] 0.642946232 0.885633597 0.403833053 0.208104583 0.513173554 0.770265069
#> [79] 0.799232253 0.603198505 0.296633975 0.808862876 0.132051619 0.652932710
#> [85] 0.374103320 0.325196402 0.876049262 0.384072141 0.856929853 0.952388958
#> [91] 0.132051619 0.462997105 0.533427017 0.296633975 0.110256532 0.564093536
#> [97] 0.154145678 0.682487962 0.885633597 0.344620752 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 184 157 88 110 32 86 168 157.1 57 76 106 97 81
#> 17.77 15.10 18.37 17.56 20.90 23.81 23.72 15.10 14.46 19.22 16.67 19.14 14.06
#> 91 68 18 187 139 32.1 171 88.1 32.2 153 81.1 8 52
#> 5.33 20.62 15.21 9.92 21.49 20.90 16.57 18.37 20.90 21.33 14.06 18.43 10.42
#> 69 111 91.1 139.1 192 188 110.1 30 61 123 170 56 192.1
#> 23.23 17.45 5.33 21.49 16.44 16.16 17.56 17.43 10.12 13.00 19.54 12.21 16.44
#> 167 113 52.1 79 18.1 167.1 192.2 15 168.1 68.1 164 25 36
#> 15.55 22.86 10.42 16.23 15.21 15.55 16.44 22.68 23.72 20.62 23.60 6.32 21.19
#> 190 88.2 158 128 129 194 32.3 79.1 140 51 177 91.2 177.1
#> 20.81 18.37 20.14 20.35 23.41 22.40 20.90 16.23 12.68 18.23 12.53 5.33 12.53
#> 169 113.1 37 40 60 93 49 100 52.2 88.3 90 30.1 123.1
#> 22.41 22.86 12.52 18.00 13.15 10.33 12.19 16.07 10.42 18.37 20.94 17.43 13.00
#> 154 5 158.1 177.2 136 125 179 170.1 107 8.1 49.1 183 136.1
#> 12.63 16.43 20.14 12.53 21.83 15.65 18.63 19.54 11.18 18.43 12.19 9.24 21.83
#> 184.1 23 158.2 194.1 85 197 29 52.3 76.1 122 38 54 131
#> 17.77 16.92 20.14 22.40 16.44 21.60 15.45 10.42 19.22 24.00 24.00 24.00 24.00
#> 27 21 144 3 104 47 173 34 27.1 143 119 200 146
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 38.1 142 21.1 112 35 34.1 193 185 156 19 94 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 34.2 174 196.1 38.2 44 135 141 21.2 65 9 163 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 3.1 72 72.1 71 9.1 71.1 121.1 35.1 174.1 122.1 132 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146.1 161 65.1 176 64 147 72.2 176.1 138 186 198 2 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196.2 198.1 162 31 9.2 131.1 143.1 144.1 67 131.2 11 46 196.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 132.1 31.1 156.1 95
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[21]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0147797 0.8580765 0.2906595
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.83386870 0.01486669 0.33647341
#> grade_iii, Cure model
#> 0.65692735
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 8 18.43 1 32 0 0
#> 167 15.55 1 56 1 0
#> 129 23.41 1 53 1 0
#> 59 10.16 1 NA 1 0
#> 90 20.94 1 50 0 1
#> 70 7.38 1 30 1 0
#> 136 21.83 1 43 0 1
#> 13 14.34 1 54 0 1
#> 123 13.00 1 44 1 0
#> 59.1 10.16 1 NA 1 0
#> 57 14.46 1 45 0 1
#> 113 22.86 1 34 0 0
#> 154 12.63 1 20 1 0
#> 168 23.72 1 70 0 0
#> 92 22.92 1 47 0 1
#> 57.1 14.46 1 45 0 1
#> 88 18.37 1 47 0 0
#> 52 10.42 1 52 0 1
#> 114 13.68 1 NA 0 0
#> 43 12.10 1 61 0 1
#> 6 15.64 1 39 0 0
#> 192 16.44 1 31 1 0
#> 154.1 12.63 1 20 1 0
#> 63 22.77 1 31 1 0
#> 145 10.07 1 65 1 0
#> 10 10.53 1 34 0 0
#> 70.1 7.38 1 30 1 0
#> 150 20.33 1 48 0 0
#> 158 20.14 1 74 1 0
#> 50 10.02 1 NA 1 0
#> 49 12.19 1 48 1 0
#> 164 23.60 1 76 0 1
#> 60 13.15 1 38 1 0
#> 77 7.27 1 67 0 1
#> 125 15.65 1 67 1 0
#> 190 20.81 1 42 1 0
#> 79 16.23 1 54 1 0
#> 154.2 12.63 1 20 1 0
#> 150.1 20.33 1 48 0 0
#> 70.2 7.38 1 30 1 0
#> 79.1 16.23 1 54 1 0
#> 155 13.08 1 26 0 0
#> 194 22.40 1 38 0 1
#> 149 8.37 1 33 1 0
#> 60.1 13.15 1 38 1 0
#> 180 14.82 1 37 0 0
#> 76 19.22 1 54 0 1
#> 140 12.68 1 59 1 0
#> 125.1 15.65 1 67 1 0
#> 49.1 12.19 1 48 1 0
#> 107 11.18 1 54 1 0
#> 136.1 21.83 1 43 0 1
#> 189 10.51 1 NA 1 0
#> 50.1 10.02 1 NA 1 0
#> 57.2 14.46 1 45 0 1
#> 85 16.44 1 36 0 0
#> 195 11.76 1 NA 1 0
#> 43.1 12.10 1 61 0 1
#> 39 15.59 1 37 0 1
#> 117 17.46 1 26 0 1
#> 45 17.42 1 54 0 1
#> 45.1 17.42 1 54 0 1
#> 197 21.60 1 69 1 0
#> 23 16.92 1 61 0 0
#> 8.1 18.43 1 32 0 0
#> 24 23.89 1 38 0 0
#> 37 12.52 1 57 1 0
#> 117.1 17.46 1 26 0 1
#> 199 19.81 1 NA 0 1
#> 15 22.68 1 48 0 0
#> 181 16.46 1 45 0 1
#> 6.1 15.64 1 39 0 0
#> 51 18.23 1 83 0 1
#> 86 23.81 1 58 0 1
#> 100 16.07 1 60 0 0
#> 179 18.63 1 42 0 0
#> 88.1 18.37 1 47 0 0
#> 197.1 21.60 1 69 1 0
#> 58 19.34 1 39 0 0
#> 159 10.55 1 50 0 1
#> 66 22.13 1 53 0 0
#> 26 15.77 1 49 0 1
#> 153 21.33 1 55 1 0
#> 86.1 23.81 1 58 0 1
#> 85.1 16.44 1 36 0 0
#> 15.1 22.68 1 48 0 0
#> 99 21.19 1 38 0 1
#> 124 9.73 1 NA 1 0
#> 41 18.02 1 40 1 0
#> 18 15.21 1 49 1 0
#> 190.1 20.81 1 42 1 0
#> 169 22.41 1 46 0 0
#> 175 21.91 1 43 0 0
#> 199.1 19.81 1 NA 0 1
#> 50.2 10.02 1 NA 1 0
#> 29 15.45 1 68 1 0
#> 32 20.90 1 37 1 0
#> 4 17.64 1 NA 0 1
#> 93 10.33 1 52 0 1
#> 18.1 15.21 1 49 1 0
#> 145.1 10.07 1 65 1 0
#> 30 17.43 1 78 0 0
#> 68 20.62 1 44 0 0
#> 183 9.24 1 67 1 0
#> 158.1 20.14 1 74 1 0
#> 55 19.34 1 69 0 1
#> 168.1 23.72 1 70 0 0
#> 81 14.06 1 34 0 0
#> 25 6.32 1 34 1 0
#> 189.1 10.51 1 NA 1 0
#> 66.1 22.13 1 53 0 0
#> 114.1 13.68 1 NA 0 0
#> 71 24.00 0 51 0 0
#> 31 24.00 0 36 0 1
#> 122 24.00 0 66 0 0
#> 135 24.00 0 58 1 0
#> 132 24.00 0 55 0 0
#> 22 24.00 0 52 1 0
#> 196 24.00 0 19 0 0
#> 72 24.00 0 40 0 1
#> 75 24.00 0 21 1 0
#> 178 24.00 0 52 1 0
#> 65 24.00 0 57 1 0
#> 1 24.00 0 23 1 0
#> 98 24.00 0 34 1 0
#> 95 24.00 0 68 0 1
#> 83 24.00 0 6 0 0
#> 12 24.00 0 63 0 0
#> 83.1 24.00 0 6 0 0
#> 142 24.00 0 53 0 0
#> 1.1 24.00 0 23 1 0
#> 73 24.00 0 NA 0 1
#> 104 24.00 0 50 1 0
#> 142.1 24.00 0 53 0 0
#> 28 24.00 0 67 1 0
#> 62 24.00 0 71 0 0
#> 98.1 24.00 0 34 1 0
#> 35 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 173 24.00 0 19 0 1
#> 138 24.00 0 44 1 0
#> 191 24.00 0 60 0 1
#> 182 24.00 0 35 0 0
#> 102 24.00 0 49 0 0
#> 152 24.00 0 36 0 1
#> 132.1 24.00 0 55 0 0
#> 156 24.00 0 50 1 0
#> 72.1 24.00 0 40 0 1
#> 122.1 24.00 0 66 0 0
#> 71.1 24.00 0 51 0 0
#> 142.2 24.00 0 53 0 0
#> 47 24.00 0 38 0 1
#> 118 24.00 0 44 1 0
#> 151 24.00 0 42 0 0
#> 115 24.00 0 NA 1 0
#> 146 24.00 0 63 1 0
#> 185 24.00 0 44 1 0
#> 11 24.00 0 42 0 1
#> 160 24.00 0 31 1 0
#> 75.1 24.00 0 21 1 0
#> 104.1 24.00 0 50 1 0
#> 121 24.00 0 57 1 0
#> 102.1 24.00 0 49 0 0
#> 33 24.00 0 53 0 0
#> 193 24.00 0 45 0 1
#> 74 24.00 0 43 0 1
#> 144 24.00 0 28 0 1
#> 162 24.00 0 51 0 0
#> 162.1 24.00 0 51 0 0
#> 156.1 24.00 0 50 1 0
#> 178.1 24.00 0 52 1 0
#> 119 24.00 0 17 0 0
#> 46 24.00 0 71 0 0
#> 138.1 24.00 0 44 1 0
#> 11.1 24.00 0 42 0 1
#> 141 24.00 0 44 1 0
#> 115.1 24.00 0 NA 1 0
#> 143 24.00 0 51 0 0
#> 2 24.00 0 9 0 0
#> 161 24.00 0 45 0 0
#> 87 24.00 0 27 0 0
#> 162.2 24.00 0 51 0 0
#> 138.2 24.00 0 44 1 0
#> 31.1 24.00 0 36 0 1
#> 22.1 24.00 0 52 1 0
#> 109 24.00 0 48 0 0
#> 165 24.00 0 47 0 0
#> 118.1 24.00 0 44 1 0
#> 64 24.00 0 43 0 0
#> 120 24.00 0 68 0 1
#> 73.1 24.00 0 NA 0 1
#> 141.1 24.00 0 44 1 0
#> 141.2 24.00 0 44 1 0
#> 104.2 24.00 0 50 1 0
#> 109.1 24.00 0 48 0 0
#> 143.1 24.00 0 51 0 0
#> 148 24.00 0 61 1 0
#> 64.1 24.00 0 43 0 0
#> 186 24.00 0 45 1 0
#> 47.1 24.00 0 38 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.834 NA NA NA
#> 2 age, Cure model 0.0149 NA NA NA
#> 3 grade_ii, Cure model 0.336 NA NA NA
#> 4 grade_iii, Cure model 0.657 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0148 NA NA NA
#> 2 grade_ii, Survival model 0.858 NA NA NA
#> 3 grade_iii, Survival model 0.291 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.83387 0.01487 0.33647 0.65693
#>
#> Degrees of Freedom: 181 Total (i.e. Null); 178 Residual
#> Null Deviance: 251.2
#> Residual Deviance: 246.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.83386870 0.01486669 0.33647341 0.65692735
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0147797 0.8580765 0.2906595
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.2567609023 0.5402262153 0.0177148496 0.1388337835 0.9386719686
#> [6] 0.0883941518 0.6393827289 0.7031267601 0.6020219252 0.0284038672
#> [11] 0.7286347626 0.0054510781 0.0228500337 0.6020219252 0.2769906429
#> [16] 0.8630684178 0.8012799001 0.5033944065 0.3979397907 0.7286347626
#> [21] 0.0344252241 0.8882500250 0.8505810262 0.9386719686 0.1819058629
#> [26] 0.1997597530 0.7770822272 0.0124738708 0.6650940796 0.9752270842
#> [31] 0.4794880722 0.1565992508 0.4323534059 0.7286347626 0.1819058629
#> [36] 0.9386719686 0.4323534059 0.6903207051 0.0586114090 0.9260697549
#> [41] 0.6650940796 0.5895486221 0.2369087183 0.7158791872 0.4794880722
#> [46] 0.7770822272 0.8258163305 0.0883941518 0.6020219252 0.3979397907
#> [51] 0.8012799001 0.5278088043 0.3197299780 0.3522245911 0.3522245911
#> [56] 0.1047115988 0.3746451452 0.2567609023 0.0002921234 0.7648260914
#> [61] 0.3197299780 0.0399729324 0.3862376117 0.5033944065 0.2979886707
#> [66] 0.0016869922 0.4555347087 0.2467424713 0.2769906429 0.1047115988
#> [71] 0.2179559131 0.8381656316 0.0655432813 0.4674574116 0.1214225229
#> [76] 0.0016869922 0.3979397907 0.0399729324 0.1300589173 0.3089178042
#> [81] 0.5650816502 0.1565992508 0.0518694886 0.0802827232 0.5526348316
#> [86] 0.1478138407 0.8756248304 0.5650816502 0.8882500250 0.3411162489
#> [91] 0.1731946482 0.9133902034 0.1997597530 0.2179559131 0.0054510781
#> [96] 0.6521883562 0.9876467054 0.0655432813 0.0000000000 0.0000000000
#> [101] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000
#>
#> $Time
#> 8 167 129 90 70 136 13 123 57 113 154 168 92
#> 18.43 15.55 23.41 20.94 7.38 21.83 14.34 13.00 14.46 22.86 12.63 23.72 22.92
#> 57.1 88 52 43 6 192 154.1 63 145 10 70.1 150 158
#> 14.46 18.37 10.42 12.10 15.64 16.44 12.63 22.77 10.07 10.53 7.38 20.33 20.14
#> 49 164 60 77 125 190 79 154.2 150.1 70.2 79.1 155 194
#> 12.19 23.60 13.15 7.27 15.65 20.81 16.23 12.63 20.33 7.38 16.23 13.08 22.40
#> 149 60.1 180 76 140 125.1 49.1 107 136.1 57.2 85 43.1 39
#> 8.37 13.15 14.82 19.22 12.68 15.65 12.19 11.18 21.83 14.46 16.44 12.10 15.59
#> 117 45 45.1 197 23 8.1 24 37 117.1 15 181 6.1 51
#> 17.46 17.42 17.42 21.60 16.92 18.43 23.89 12.52 17.46 22.68 16.46 15.64 18.23
#> 86 100 179 88.1 197.1 58 159 66 26 153 86.1 85.1 15.1
#> 23.81 16.07 18.63 18.37 21.60 19.34 10.55 22.13 15.77 21.33 23.81 16.44 22.68
#> 99 41 18 190.1 169 175 29 32 93 18.1 145.1 30 68
#> 21.19 18.02 15.21 20.81 22.41 21.91 15.45 20.90 10.33 15.21 10.07 17.43 20.62
#> 183 158.1 55 168.1 81 25 66.1 71 31 122 135 132 22
#> 9.24 20.14 19.34 23.72 14.06 6.32 22.13 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 72 75 178 65 1 98 95 83 12 83.1 142 1.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 142.1 28 62 98.1 35 19 173 138 191 182 102 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.1 156 72.1 122.1 71.1 142.2 47 118 151 146 185 11 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75.1 104.1 121 102.1 33 193 74 144 162 162.1 156.1 178.1 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46 138.1 11.1 141 143 2 161 87 162.2 138.2 31.1 22.1 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 118.1 64 120 141.1 141.2 104.2 109.1 143.1 148 64.1 186 47.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[22]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.001579847 0.784984794 0.202945187
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.09615188 0.01643662 0.43223502
#> grade_iii, Cure model
#> 1.19902372
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 13 14.34 1 54 0 1
#> 79 16.23 1 54 1 0
#> 16 8.71 1 71 0 1
#> 76 19.22 1 54 0 1
#> 179 18.63 1 42 0 0
#> 108 18.29 1 39 0 1
#> 81 14.06 1 34 0 0
#> 171 16.57 1 41 0 1
#> 93 10.33 1 52 0 1
#> 58 19.34 1 39 0 0
#> 89 11.44 1 NA 0 0
#> 167 15.55 1 56 1 0
#> 93.1 10.33 1 52 0 1
#> 86 23.81 1 58 0 1
#> 91 5.33 1 61 0 1
#> 37 12.52 1 57 1 0
#> 124 9.73 1 NA 1 0
#> 58.1 19.34 1 39 0 0
#> 197 21.60 1 69 1 0
#> 199 19.81 1 NA 0 1
#> 113 22.86 1 34 0 0
#> 194 22.40 1 38 0 1
#> 49 12.19 1 48 1 0
#> 10 10.53 1 34 0 0
#> 175 21.91 1 43 0 0
#> 60 13.15 1 38 1 0
#> 106 16.67 1 49 1 0
#> 85 16.44 1 36 0 0
#> 188 16.16 1 46 0 1
#> 123 13.00 1 44 1 0
#> 106.1 16.67 1 49 1 0
#> 69 23.23 1 25 0 1
#> 26 15.77 1 49 0 1
#> 56 12.21 1 60 0 0
#> 40 18.00 1 28 1 0
#> 36 21.19 1 48 0 1
#> 36.1 21.19 1 48 0 1
#> 175.1 21.91 1 43 0 0
#> 175.2 21.91 1 43 0 0
#> 166 19.98 1 48 0 0
#> 45 17.42 1 54 0 1
#> 114 13.68 1 NA 0 0
#> 153 21.33 1 55 1 0
#> 61 10.12 1 36 0 1
#> 29 15.45 1 68 1 0
#> 91.1 5.33 1 61 0 1
#> 177 12.53 1 75 0 0
#> 42 12.43 1 49 0 1
#> 164 23.60 1 76 0 1
#> 39 15.59 1 37 0 1
#> 55 19.34 1 69 0 1
#> 183 9.24 1 67 1 0
#> 158 20.14 1 74 1 0
#> 97 19.14 1 65 0 1
#> 183.1 9.24 1 67 1 0
#> 10.1 10.53 1 34 0 0
#> 134 17.81 1 47 1 0
#> 92 22.92 1 47 0 1
#> 157 15.10 1 47 0 0
#> 123.1 13.00 1 44 1 0
#> 114.1 13.68 1 NA 0 0
#> 6 15.64 1 39 0 0
#> 49.1 12.19 1 48 1 0
#> 10.2 10.53 1 34 0 0
#> 175.3 21.91 1 43 0 0
#> 13.1 14.34 1 54 0 1
#> 114.2 13.68 1 NA 0 0
#> 40.1 18.00 1 28 1 0
#> 194.1 22.40 1 38 0 1
#> 188.1 16.16 1 46 0 1
#> 177.1 12.53 1 75 0 0
#> 128 20.35 1 35 0 1
#> 43 12.10 1 61 0 1
#> 127 3.53 1 62 0 1
#> 128.1 20.35 1 35 0 1
#> 16.1 8.71 1 71 0 1
#> 171.1 16.57 1 41 0 1
#> 90 20.94 1 50 0 1
#> 61.1 10.12 1 36 0 1
#> 167.1 15.55 1 56 1 0
#> 25 6.32 1 34 1 0
#> 180 14.82 1 37 0 0
#> 43.1 12.10 1 61 0 1
#> 159 10.55 1 50 0 1
#> 114.3 13.68 1 NA 0 0
#> 123.2 13.00 1 44 1 0
#> 37.1 12.52 1 57 1 0
#> 23 16.92 1 61 0 0
#> 187 9.92 1 39 1 0
#> 29.1 15.45 1 68 1 0
#> 61.2 10.12 1 36 0 1
#> 85.1 16.44 1 36 0 0
#> 51 18.23 1 83 0 1
#> 8 18.43 1 32 0 0
#> 107 11.18 1 54 1 0
#> 15 22.68 1 48 0 0
#> 169 22.41 1 46 0 0
#> 167.2 15.55 1 56 1 0
#> 26.1 15.77 1 49 0 1
#> 150 20.33 1 48 0 0
#> 133 14.65 1 57 0 0
#> 69.1 23.23 1 25 0 1
#> 168 23.72 1 70 0 0
#> 70 7.38 1 30 1 0
#> 16.2 8.71 1 71 0 1
#> 57 14.46 1 45 0 1
#> 93.2 10.33 1 52 0 1
#> 49.2 12.19 1 48 1 0
#> 101 9.97 1 10 0 1
#> 101.1 9.97 1 10 0 1
#> 171.2 16.57 1 41 0 1
#> 183.2 9.24 1 67 1 0
#> 162 24.00 0 51 0 0
#> 72 24.00 0 40 0 1
#> 118 24.00 0 44 1 0
#> 162.1 24.00 0 51 0 0
#> 172 24.00 0 41 0 0
#> 143 24.00 0 51 0 0
#> 142 24.00 0 53 0 0
#> 143.1 24.00 0 51 0 0
#> 74 24.00 0 43 0 1
#> 156 24.00 0 50 1 0
#> 151 24.00 0 42 0 0
#> 151.1 24.00 0 42 0 0
#> 178 24.00 0 52 1 0
#> 11 24.00 0 42 0 1
#> 165 24.00 0 47 0 0
#> 138 24.00 0 44 1 0
#> 22 24.00 0 52 1 0
#> 65 24.00 0 57 1 0
#> 163 24.00 0 66 0 0
#> 146 24.00 0 63 1 0
#> 132 24.00 0 55 0 0
#> 193 24.00 0 45 0 1
#> 142.1 24.00 0 53 0 0
#> 200 24.00 0 64 0 0
#> 44 24.00 0 56 0 0
#> 98 24.00 0 34 1 0
#> 163.1 24.00 0 66 0 0
#> 121 24.00 0 57 1 0
#> 176 24.00 0 43 0 1
#> 102 24.00 0 49 0 0
#> 84 24.00 0 39 0 1
#> 151.2 24.00 0 42 0 0
#> 87 24.00 0 27 0 0
#> 20 24.00 0 46 1 0
#> 165.1 24.00 0 47 0 0
#> 109 24.00 0 48 0 0
#> 47 24.00 0 38 0 1
#> 103 24.00 0 56 1 0
#> 115 24.00 0 NA 1 0
#> 47.1 24.00 0 38 0 1
#> 80 24.00 0 41 0 0
#> 46 24.00 0 71 0 0
#> 141 24.00 0 44 1 0
#> 147 24.00 0 76 1 0
#> 104 24.00 0 50 1 0
#> 200.1 24.00 0 64 0 0
#> 196 24.00 0 19 0 0
#> 141.1 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 200.2 24.00 0 64 0 0
#> 71 24.00 0 51 0 0
#> 87.1 24.00 0 27 0 0
#> 118.1 24.00 0 44 1 0
#> 196.1 24.00 0 19 0 0
#> 73.1 24.00 0 NA 0 1
#> 144 24.00 0 28 0 1
#> 196.2 24.00 0 19 0 0
#> 193.1 24.00 0 45 0 1
#> 21 24.00 0 47 0 0
#> 144.1 24.00 0 28 0 1
#> 147.1 24.00 0 76 1 0
#> 19 24.00 0 57 0 1
#> 193.2 24.00 0 45 0 1
#> 147.2 24.00 0 76 1 0
#> 74.1 24.00 0 43 0 1
#> 31 24.00 0 36 0 1
#> 156.1 24.00 0 50 1 0
#> 67 24.00 0 25 0 0
#> 2 24.00 0 9 0 0
#> 20.1 24.00 0 46 1 0
#> 200.3 24.00 0 64 0 0
#> 165.2 24.00 0 47 0 0
#> 67.1 24.00 0 25 0 0
#> 2.1 24.00 0 9 0 0
#> 94 24.00 0 51 0 1
#> 132.1 24.00 0 55 0 0
#> 193.3 24.00 0 45 0 1
#> 1 24.00 0 23 1 0
#> 137 24.00 0 45 1 0
#> 135 24.00 0 58 1 0
#> 146.1 24.00 0 63 1 0
#> 119 24.00 0 17 0 0
#> 82 24.00 0 34 0 0
#> 144.2 24.00 0 28 0 1
#> 137.1 24.00 0 45 1 0
#> 162.2 24.00 0 51 0 0
#> 84.1 24.00 0 39 0 1
#> 72.1 24.00 0 40 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.10 NA NA NA
#> 2 age, Cure model 0.0164 NA NA NA
#> 3 grade_ii, Cure model 0.432 NA NA NA
#> 4 grade_iii, Cure model 1.20 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00158 NA NA NA
#> 2 grade_ii, Survival model 0.785 NA NA NA
#> 3 grade_iii, Survival model 0.203 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.09615 0.01644 0.43224 1.19902
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.3
#> Residual Deviance: 247.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.09615188 0.01643662 0.43223502 1.19902372
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.001579847 0.784984794 0.202945187
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.67258765 0.53167991 0.94278265 0.35192327 0.37351366 0.39512526
#> [7] 0.68946281 0.48529279 0.85386950 0.32035600 0.59572781 0.85386950
#> [13] 0.01014272 0.97869207 0.74644051 0.32035600 0.20773725 0.09455419
#> [19] 0.13514377 0.77805555 0.83130038 0.16032843 0.69795813 0.46648037
#> [25] 0.51300026 0.54093703 0.70634477 0.46648037 0.05630644 0.55920667
#> [31] 0.77013115 0.41664120 0.23164909 0.23164909 0.16032843 0.16032843
#> [37] 0.30947637 0.44666252 0.22002082 0.87636233 0.62158944 0.97869207
#> [43] 0.73032515 0.76221413 0.04077920 0.58657347 0.32035600 0.92115030
#> [49] 0.29862464 0.36273539 0.92115030 0.83130038 0.43673603 0.08124526
#> [55] 0.63849480 0.70634477 0.57739687 0.77805555 0.83130038 0.16032843
#> [61] 0.67258765 0.41664120 0.13514377 0.54093703 0.73032515 0.26540628
#> [67] 0.80087510 0.99288410 0.26540628 0.94278265 0.48529279 0.25402699
#> [73] 0.87636233 0.59572781 0.97155847 0.64701231 0.80087510 0.82371908
#> [79] 0.70634477 0.74644051 0.45656156 0.91371114 0.62158944 0.87636233
#> [85] 0.51300026 0.40589383 0.38431196 0.81612857 0.10796484 0.12150029
#> [91] 0.59572781 0.55920667 0.28738478 0.65553620 0.05630644 0.02481415
#> [97] 0.96436797 0.94278265 0.66406963 0.85386950 0.77805555 0.89876476
#> [103] 0.89876476 0.48529279 0.92115030 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 13 79 16 76 179 108 81 171 93 58 167 93.1 86
#> 14.34 16.23 8.71 19.22 18.63 18.29 14.06 16.57 10.33 19.34 15.55 10.33 23.81
#> 91 37 58.1 197 113 194 49 10 175 60 106 85 188
#> 5.33 12.52 19.34 21.60 22.86 22.40 12.19 10.53 21.91 13.15 16.67 16.44 16.16
#> 123 106.1 69 26 56 40 36 36.1 175.1 175.2 166 45 153
#> 13.00 16.67 23.23 15.77 12.21 18.00 21.19 21.19 21.91 21.91 19.98 17.42 21.33
#> 61 29 91.1 177 42 164 39 55 183 158 97 183.1 10.1
#> 10.12 15.45 5.33 12.53 12.43 23.60 15.59 19.34 9.24 20.14 19.14 9.24 10.53
#> 134 92 157 123.1 6 49.1 10.2 175.3 13.1 40.1 194.1 188.1 177.1
#> 17.81 22.92 15.10 13.00 15.64 12.19 10.53 21.91 14.34 18.00 22.40 16.16 12.53
#> 128 43 127 128.1 16.1 171.1 90 61.1 167.1 25 180 43.1 159
#> 20.35 12.10 3.53 20.35 8.71 16.57 20.94 10.12 15.55 6.32 14.82 12.10 10.55
#> 123.2 37.1 23 187 29.1 61.2 85.1 51 8 107 15 169 167.2
#> 13.00 12.52 16.92 9.92 15.45 10.12 16.44 18.23 18.43 11.18 22.68 22.41 15.55
#> 26.1 150 133 69.1 168 70 16.2 57 93.2 49.2 101 101.1 171.2
#> 15.77 20.33 14.65 23.23 23.72 7.38 8.71 14.46 10.33 12.19 9.97 9.97 16.57
#> 183.2 162 72 118 162.1 172 143 142 143.1 74 156 151 151.1
#> 9.24 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 11 165 138 22 65 163 146 132 193 142.1 200 44
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 163.1 121 176 102 84 151.2 87 20 165.1 109 47 103
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47.1 80 46 141 147 104 200.1 196 141.1 200.2 71 87.1 118.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196.1 144 196.2 193.1 21 144.1 147.1 19 193.2 147.2 74.1 31 156.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 2 20.1 200.3 165.2 67.1 2.1 94 132.1 193.3 1 137 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146.1 119 82 144.2 137.1 162.2 84.1 72.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[23]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01327016 0.49229325 0.42597078
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.384474746 0.001500437 -0.725978983
#> grade_iii, Cure model
#> 0.048846167
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 110 17.56 1 65 0 1
#> 36 21.19 1 48 0 1
#> 134 17.81 1 47 1 0
#> 32 20.90 1 37 1 0
#> 76 19.22 1 54 0 1
#> 157 15.10 1 47 0 0
#> 79 16.23 1 54 1 0
#> 179 18.63 1 42 0 0
#> 66 22.13 1 53 0 0
#> 140 12.68 1 59 1 0
#> 168 23.72 1 70 0 0
#> 60 13.15 1 38 1 0
#> 39 15.59 1 37 0 1
#> 41 18.02 1 40 1 0
#> 69 23.23 1 25 0 1
#> 140.1 12.68 1 59 1 0
#> 30 17.43 1 78 0 0
#> 195 11.76 1 NA 1 0
#> 26 15.77 1 49 0 1
#> 40 18.00 1 28 1 0
#> 184 17.77 1 38 0 0
#> 97 19.14 1 65 0 1
#> 97.1 19.14 1 65 0 1
#> 15 22.68 1 48 0 0
#> 99 21.19 1 38 0 1
#> 159 10.55 1 50 0 1
#> 42 12.43 1 49 0 1
#> 129 23.41 1 53 1 0
#> 26.1 15.77 1 49 0 1
#> 24 23.89 1 38 0 0
#> 117 17.46 1 26 0 1
#> 101 9.97 1 10 0 1
#> 183 9.24 1 67 1 0
#> 91 5.33 1 61 0 1
#> 105 19.75 1 60 0 0
#> 15.1 22.68 1 48 0 0
#> 134.1 17.81 1 47 1 0
#> 81 14.06 1 34 0 0
#> 184.1 17.77 1 38 0 0
#> 140.2 12.68 1 59 1 0
#> 36.1 21.19 1 48 0 1
#> 157.1 15.10 1 47 0 0
#> 26.2 15.77 1 49 0 1
#> 37 12.52 1 57 1 0
#> 89 11.44 1 NA 0 0
#> 136 21.83 1 43 0 1
#> 8 18.43 1 32 0 0
#> 194 22.40 1 38 0 1
#> 166 19.98 1 48 0 0
#> 26.3 15.77 1 49 0 1
#> 194.1 22.40 1 38 0 1
#> 13 14.34 1 54 0 1
#> 188 16.16 1 46 0 1
#> 66.1 22.13 1 53 0 0
#> 6 15.64 1 39 0 0
#> 76.1 19.22 1 54 0 1
#> 59 10.16 1 NA 1 0
#> 77 7.27 1 67 0 1
#> 68 20.62 1 44 0 0
#> 180 14.82 1 37 0 0
#> 166.1 19.98 1 48 0 0
#> 25 6.32 1 34 1 0
#> 187 9.92 1 39 1 0
#> 89.1 11.44 1 NA 0 0
#> 133 14.65 1 57 0 0
#> 30.1 17.43 1 78 0 0
#> 14 12.89 1 21 0 0
#> 15.2 22.68 1 48 0 0
#> 25.1 6.32 1 34 1 0
#> 127 3.53 1 62 0 1
#> 70 7.38 1 30 1 0
#> 26.4 15.77 1 49 0 1
#> 91.1 5.33 1 61 0 1
#> 51 18.23 1 83 0 1
#> 179.1 18.63 1 42 0 0
#> 166.2 19.98 1 48 0 0
#> 4 17.64 1 NA 0 1
#> 106 16.67 1 49 1 0
#> 166.3 19.98 1 48 0 0
#> 39.1 15.59 1 37 0 1
#> 85 16.44 1 36 0 0
#> 96 14.54 1 33 0 1
#> 92 22.92 1 47 0 1
#> 39.2 15.59 1 37 0 1
#> 166.4 19.98 1 48 0 0
#> 153 21.33 1 55 1 0
#> 40.1 18.00 1 28 1 0
#> 55 19.34 1 69 0 1
#> 70.1 7.38 1 30 1 0
#> 55.1 19.34 1 69 0 1
#> 134.2 17.81 1 47 1 0
#> 90 20.94 1 50 0 1
#> 181 16.46 1 45 0 1
#> 180.1 14.82 1 37 0 0
#> 105.1 19.75 1 60 0 0
#> 14.1 12.89 1 21 0 0
#> 145 10.07 1 65 1 0
#> 6.1 15.64 1 39 0 0
#> 129.1 23.41 1 53 1 0
#> 129.2 23.41 1 53 1 0
#> 89.2 11.44 1 NA 0 0
#> 189 10.51 1 NA 1 0
#> 15.3 22.68 1 48 0 0
#> 10 10.53 1 34 0 0
#> 175 21.91 1 43 0 0
#> 168.1 23.72 1 70 0 0
#> 180.2 14.82 1 37 0 0
#> 40.2 18.00 1 28 1 0
#> 181.1 16.46 1 45 0 1
#> 168.2 23.72 1 70 0 0
#> 81.1 14.06 1 34 0 0
#> 15.4 22.68 1 48 0 0
#> 115 24.00 0 NA 1 0
#> 156 24.00 0 50 1 0
#> 109 24.00 0 48 0 0
#> 73 24.00 0 NA 0 1
#> 109.1 24.00 0 48 0 0
#> 31 24.00 0 36 0 1
#> 162 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 165 24.00 0 47 0 0
#> 47 24.00 0 38 0 1
#> 112 24.00 0 61 0 0
#> 53 24.00 0 32 0 1
#> 17 24.00 0 38 0 1
#> 103 24.00 0 56 1 0
#> 176 24.00 0 43 0 1
#> 178 24.00 0 52 1 0
#> 74 24.00 0 43 0 1
#> 31.1 24.00 0 36 0 1
#> 22 24.00 0 52 1 0
#> 137 24.00 0 45 1 0
#> 109.2 24.00 0 48 0 0
#> 156.1 24.00 0 50 1 0
#> 116 24.00 0 58 0 1
#> 152 24.00 0 36 0 1
#> 71 24.00 0 51 0 0
#> 126.1 24.00 0 48 0 0
#> 182 24.00 0 35 0 0
#> 174 24.00 0 49 1 0
#> 31.2 24.00 0 36 0 1
#> 33 24.00 0 53 0 0
#> 132 24.00 0 55 0 0
#> 142 24.00 0 53 0 0
#> 72 24.00 0 40 0 1
#> 152.1 24.00 0 36 0 1
#> 82 24.00 0 34 0 0
#> 104 24.00 0 50 1 0
#> 95 24.00 0 68 0 1
#> 144 24.00 0 28 0 1
#> 80 24.00 0 41 0 0
#> 137.1 24.00 0 45 1 0
#> 135 24.00 0 58 1 0
#> 115.1 24.00 0 NA 1 0
#> 104.1 24.00 0 50 1 0
#> 28 24.00 0 67 1 0
#> 121 24.00 0 57 1 0
#> 73.1 24.00 0 NA 0 1
#> 144.1 24.00 0 28 0 1
#> 138 24.00 0 44 1 0
#> 38 24.00 0 31 1 0
#> 20 24.00 0 46 1 0
#> 17.1 24.00 0 38 0 1
#> 71.1 24.00 0 51 0 0
#> 178.1 24.00 0 52 1 0
#> 162.1 24.00 0 51 0 0
#> 7 24.00 0 37 1 0
#> 44 24.00 0 56 0 0
#> 148 24.00 0 61 1 0
#> 152.2 24.00 0 36 0 1
#> 121.1 24.00 0 57 1 0
#> 75 24.00 0 21 1 0
#> 137.2 24.00 0 45 1 0
#> 118 24.00 0 44 1 0
#> 152.3 24.00 0 36 0 1
#> 131 24.00 0 66 0 0
#> 142.1 24.00 0 53 0 0
#> 84 24.00 0 39 0 1
#> 20.1 24.00 0 46 1 0
#> 121.2 24.00 0 57 1 0
#> 132.1 24.00 0 55 0 0
#> 146 24.00 0 63 1 0
#> 147 24.00 0 76 1 0
#> 65 24.00 0 57 1 0
#> 173 24.00 0 19 0 1
#> 193 24.00 0 45 0 1
#> 19 24.00 0 57 0 1
#> 71.2 24.00 0 51 0 0
#> 115.2 24.00 0 NA 1 0
#> 146.1 24.00 0 63 1 0
#> 178.2 24.00 0 52 1 0
#> 20.2 24.00 0 46 1 0
#> 142.2 24.00 0 53 0 0
#> 120 24.00 0 68 0 1
#> 20.3 24.00 0 46 1 0
#> 151 24.00 0 42 0 0
#> 65.1 24.00 0 57 1 0
#> 119 24.00 0 17 0 0
#> 103.1 24.00 0 56 1 0
#> 21 24.00 0 47 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.384 NA NA NA
#> 2 age, Cure model 0.00150 NA NA NA
#> 3 grade_ii, Cure model -0.726 NA NA NA
#> 4 grade_iii, Cure model 0.0488 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0133 NA NA NA
#> 2 grade_ii, Survival model 0.492 NA NA NA
#> 3 grade_iii, Survival model 0.426 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.38447 0.00150 -0.72598 0.04885
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 258
#> Residual Deviance: 252.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.384474746 0.001500437 -0.725978983 0.048846167
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01327016 0.49229325 0.42597078
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.3856032894 0.1028450204 0.3356674545 0.1309155695 0.2195810678
#> [6] 0.6037924867 0.4710185514 0.2566694441 0.0687307380 0.7595591581
#> [11] 0.0020823602 0.7227494047 0.5699542751 0.2962614635 0.0226853854
#> [16] 0.7595591581 0.4064602815 0.4931292952 0.3064542254 0.3651985988
#> [21] 0.2378693507 0.2378693507 0.0322245863 0.1028450204 0.8216737598
#> [26] 0.8090745717 0.0111396465 0.4931292952 0.0003976163 0.3960433530
#> [31] 0.8597934230 0.8852082243 0.9614523868 0.1843542446 0.0322245863
#> [36] 0.3356674545 0.6984180195 0.3651985988 0.7595591581 0.1028450204
#> [41] 0.6037924867 0.4931292952 0.7965146799 0.0886195763 0.2760773058
#> [46] 0.0569443594 0.1459054779 0.4931292952 0.0569443594 0.6862991917
#> [51] 0.4820525649 0.0687307380 0.5472522500 0.2195810678 0.9232654456
#> [56] 0.1383207015 0.6269732323 0.1459054779 0.9360623714 0.8724985154
#> [61] 0.6621715736 0.4064602815 0.7350217320 0.0322245863 0.9360623714
#> [66] 0.9870578179 0.8979779880 0.4931292952 0.9614523868 0.2860819665
#> [71] 0.2566694441 0.1459054779 0.4277209210 0.1459054779 0.5699542751
#> [76] 0.4600362382 0.6742340983 0.0273796034 0.5699542751 0.1459054779
#> [81] 0.0956763002 0.3064542254 0.2016696450 0.8979779880 0.2016696450
#> [86] 0.3356674545 0.1235100056 0.4385264783 0.6269732323 0.1843542446
#> [91] 0.7350217320 0.8470240283 0.5472522500 0.0111396465 0.0111396465
#> [96] 0.0322245863 0.8343139305 0.0816379738 0.0020823602 0.6269732323
#> [101] 0.3064542254 0.4385264783 0.0020823602 0.6984180195 0.0322245863
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 110 36 134 32 76 157 79 179 66 140 168 60 39
#> 17.56 21.19 17.81 20.90 19.22 15.10 16.23 18.63 22.13 12.68 23.72 13.15 15.59
#> 41 69 140.1 30 26 40 184 97 97.1 15 99 159 42
#> 18.02 23.23 12.68 17.43 15.77 18.00 17.77 19.14 19.14 22.68 21.19 10.55 12.43
#> 129 26.1 24 117 101 183 91 105 15.1 134.1 81 184.1 140.2
#> 23.41 15.77 23.89 17.46 9.97 9.24 5.33 19.75 22.68 17.81 14.06 17.77 12.68
#> 36.1 157.1 26.2 37 136 8 194 166 26.3 194.1 13 188 66.1
#> 21.19 15.10 15.77 12.52 21.83 18.43 22.40 19.98 15.77 22.40 14.34 16.16 22.13
#> 6 76.1 77 68 180 166.1 25 187 133 30.1 14 15.2 25.1
#> 15.64 19.22 7.27 20.62 14.82 19.98 6.32 9.92 14.65 17.43 12.89 22.68 6.32
#> 127 70 26.4 91.1 51 179.1 166.2 106 166.3 39.1 85 96 92
#> 3.53 7.38 15.77 5.33 18.23 18.63 19.98 16.67 19.98 15.59 16.44 14.54 22.92
#> 39.2 166.4 153 40.1 55 70.1 55.1 134.2 90 181 180.1 105.1 14.1
#> 15.59 19.98 21.33 18.00 19.34 7.38 19.34 17.81 20.94 16.46 14.82 19.75 12.89
#> 145 6.1 129.1 129.2 15.3 10 175 168.1 180.2 40.2 181.1 168.2 81.1
#> 10.07 15.64 23.41 23.41 22.68 10.53 21.91 23.72 14.82 18.00 16.46 23.72 14.06
#> 15.4 156 109 109.1 31 162 126 165 47 112 53 17 103
#> 22.68 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 178 74 31.1 22 137 109.2 156.1 116 152 71 126.1 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 31.2 33 132 142 72 152.1 82 104 95 144 80 137.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 104.1 28 121 144.1 138 38 20 17.1 71.1 178.1 162.1 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 148 152.2 121.1 75 137.2 118 152.3 131 142.1 84 20.1 121.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.1 146 147 65 173 193 19 71.2 146.1 178.2 20.2 142.2 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20.3 151 65.1 119 103.1 21
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[24]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.008053431 0.317732265 0.297767616
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.172067643 0.004890612 -0.305650182
#> grade_iii, Cure model
#> 0.927961380
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 60 13.15 1 38 1 0
#> 183 9.24 1 67 1 0
#> 68 20.62 1 44 0 0
#> 113 22.86 1 34 0 0
#> 133 14.65 1 57 0 0
#> 88 18.37 1 47 0 0
#> 4 17.64 1 NA 0 1
#> 133.1 14.65 1 57 0 0
#> 37 12.52 1 57 1 0
#> 57 14.46 1 45 0 1
#> 29 15.45 1 68 1 0
#> 171 16.57 1 41 0 1
#> 18 15.21 1 49 1 0
#> 13 14.34 1 54 0 1
#> 58 19.34 1 39 0 0
#> 52 10.42 1 52 0 1
#> 199 19.81 1 NA 0 1
#> 114 13.68 1 NA 0 0
#> 4.1 17.64 1 NA 0 1
#> 69 23.23 1 25 0 1
#> 155 13.08 1 26 0 0
#> 23 16.92 1 61 0 0
#> 136 21.83 1 43 0 1
#> 175 21.91 1 43 0 0
#> 108 18.29 1 39 0 1
#> 149 8.37 1 33 1 0
#> 59 10.16 1 NA 1 0
#> 49 12.19 1 48 1 0
#> 166 19.98 1 48 0 0
#> 61 10.12 1 36 0 1
#> 63 22.77 1 31 1 0
#> 56 12.21 1 60 0 0
#> 101 9.97 1 10 0 1
#> 100 16.07 1 60 0 0
#> 197 21.60 1 69 1 0
#> 129 23.41 1 53 1 0
#> 88.1 18.37 1 47 0 0
#> 25 6.32 1 34 1 0
#> 139 21.49 1 63 1 0
#> 158 20.14 1 74 1 0
#> 56.1 12.21 1 60 0 0
#> 175.1 21.91 1 43 0 0
#> 149.1 8.37 1 33 1 0
#> 58.1 19.34 1 39 0 0
#> 166.1 19.98 1 48 0 0
#> 51 18.23 1 83 0 1
#> 155.1 13.08 1 26 0 0
#> 23.1 16.92 1 61 0 0
#> 61.1 10.12 1 36 0 1
#> 155.2 13.08 1 26 0 0
#> 88.2 18.37 1 47 0 0
#> 81 14.06 1 34 0 0
#> 45 17.42 1 54 0 1
#> 59.1 10.16 1 NA 1 0
#> 195 11.76 1 NA 1 0
#> 101.1 9.97 1 10 0 1
#> 125 15.65 1 67 1 0
#> 111 17.45 1 47 0 1
#> 154 12.63 1 20 1 0
#> 199.1 19.81 1 NA 0 1
#> 106 16.67 1 49 1 0
#> 49.1 12.19 1 48 1 0
#> 55 19.34 1 69 0 1
#> 145 10.07 1 65 1 0
#> 59.2 10.16 1 NA 1 0
#> 55.1 19.34 1 69 0 1
#> 183.1 9.24 1 67 1 0
#> 49.2 12.19 1 48 1 0
#> 189 10.51 1 NA 1 0
#> 26 15.77 1 49 0 1
#> 157 15.10 1 47 0 0
#> 167 15.55 1 56 1 0
#> 85 16.44 1 36 0 0
#> 150 20.33 1 48 0 0
#> 45.1 17.42 1 54 0 1
#> 58.2 19.34 1 39 0 0
#> 114.1 13.68 1 NA 0 0
#> 101.2 9.97 1 10 0 1
#> 70 7.38 1 30 1 0
#> 183.2 9.24 1 67 1 0
#> 43 12.10 1 61 0 1
#> 97 19.14 1 65 0 1
#> 133.2 14.65 1 57 0 0
#> 81.1 14.06 1 34 0 0
#> 70.1 7.38 1 30 1 0
#> 85.1 16.44 1 36 0 0
#> 139.1 21.49 1 63 1 0
#> 30 17.43 1 78 0 0
#> 111.1 17.45 1 47 0 1
#> 101.3 9.97 1 10 0 1
#> 45.2 17.42 1 54 0 1
#> 108.1 18.29 1 39 0 1
#> 154.1 12.63 1 20 1 0
#> 177 12.53 1 75 0 0
#> 66 22.13 1 53 0 0
#> 130 16.47 1 53 0 1
#> 77 7.27 1 67 0 1
#> 159 10.55 1 50 0 1
#> 52.1 10.42 1 52 0 1
#> 41 18.02 1 40 1 0
#> 57.1 14.46 1 45 0 1
#> 93 10.33 1 52 0 1
#> 129.1 23.41 1 53 1 0
#> 81.2 14.06 1 34 0 0
#> 91 5.33 1 61 0 1
#> 188 16.16 1 46 0 1
#> 92 22.92 1 47 0 1
#> 171.1 16.57 1 41 0 1
#> 99 21.19 1 38 0 1
#> 171.2 16.57 1 41 0 1
#> 175.2 21.91 1 43 0 0
#> 145.1 10.07 1 65 1 0
#> 173 24.00 0 19 0 1
#> 126 24.00 0 48 0 0
#> 138 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 142 24.00 0 53 0 0
#> 121 24.00 0 57 1 0
#> 143 24.00 0 51 0 0
#> 84 24.00 0 39 0 1
#> 72 24.00 0 40 0 1
#> 71 24.00 0 51 0 0
#> 1 24.00 0 23 1 0
#> 87 24.00 0 27 0 0
#> 178 24.00 0 52 1 0
#> 173.1 24.00 0 19 0 1
#> 102 24.00 0 49 0 0
#> 9 24.00 0 31 1 0
#> 65 24.00 0 57 1 0
#> 7 24.00 0 37 1 0
#> 74 24.00 0 43 0 1
#> 147 24.00 0 76 1 0
#> 109 24.00 0 48 0 0
#> 109.1 24.00 0 48 0 0
#> 22 24.00 0 52 1 0
#> 1.1 24.00 0 23 1 0
#> 82 24.00 0 34 0 0
#> 27 24.00 0 63 1 0
#> 115 24.00 0 NA 1 0
#> 19 24.00 0 57 0 1
#> 73.1 24.00 0 NA 0 1
#> 54 24.00 0 53 1 0
#> 121.1 24.00 0 57 1 0
#> 83 24.00 0 6 0 0
#> 20 24.00 0 46 1 0
#> 147.1 24.00 0 76 1 0
#> 121.2 24.00 0 57 1 0
#> 200 24.00 0 64 0 0
#> 200.1 24.00 0 64 0 0
#> 7.1 24.00 0 37 1 0
#> 44 24.00 0 56 0 0
#> 137 24.00 0 45 1 0
#> 46 24.00 0 71 0 0
#> 122 24.00 0 66 0 0
#> 33 24.00 0 53 0 0
#> 115.1 24.00 0 NA 1 0
#> 22.1 24.00 0 52 1 0
#> 174 24.00 0 49 1 0
#> 20.1 24.00 0 46 1 0
#> 94 24.00 0 51 0 1
#> 186 24.00 0 45 1 0
#> 11 24.00 0 42 0 1
#> 75 24.00 0 21 1 0
#> 162 24.00 0 51 0 0
#> 138.1 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#> 142.1 24.00 0 53 0 0
#> 151 24.00 0 42 0 0
#> 17 24.00 0 38 0 1
#> 9.1 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 137.1 24.00 0 45 1 0
#> 34 24.00 0 36 0 0
#> 156 24.00 0 50 1 0
#> 132 24.00 0 55 0 0
#> 193 24.00 0 45 0 1
#> 147.2 24.00 0 76 1 0
#> 132.1 24.00 0 55 0 0
#> 142.2 24.00 0 53 0 0
#> 120 24.00 0 68 0 1
#> 138.2 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 83.1 24.00 0 6 0 0
#> 109.2 24.00 0 48 0 0
#> 146.1 24.00 0 63 1 0
#> 87.1 24.00 0 27 0 0
#> 132.2 24.00 0 55 0 0
#> 11.1 24.00 0 42 0 1
#> 22.2 24.00 0 52 1 0
#> 174.1 24.00 0 49 1 0
#> 28 24.00 0 67 1 0
#> 131 24.00 0 66 0 0
#> 33.1 24.00 0 53 0 0
#> 80 24.00 0 41 0 0
#> 142.3 24.00 0 53 0 0
#> 46.1 24.00 0 71 0 0
#> 75.1 24.00 0 21 1 0
#> 38 24.00 0 31 1 0
#> 156.1 24.00 0 50 1 0
#> 53 24.00 0 32 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.172 NA NA NA
#> 2 age, Cure model 0.00489 NA NA NA
#> 3 grade_ii, Cure model -0.306 NA NA NA
#> 4 grade_iii, Cure model 0.928 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00805 NA NA NA
#> 2 grade_ii, Survival model 0.318 NA NA NA
#> 3 grade_iii, Survival model 0.298 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.172068 0.004891 -0.305650 0.927961
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 254.9
#> Residual Deviance: 244.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.172067643 0.004890612 -0.305650182 0.927961380
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.008053431 0.317732265 0.297767616
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.590812364 0.885286949 0.103761807 0.026557081 0.492982045 0.195112469
#> [7] 0.492982045 0.668656030 0.525188757 0.461005315 0.348164380 0.471627564
#> [13] 0.546941922 0.144912735 0.759620463 0.014466362 0.601971128 0.317970254
#> [19] 0.066005146 0.046225766 0.222428363 0.919522837 0.702678015 0.128185789
#> [25] 0.794166340 0.033041362 0.679963663 0.840280066 0.418932801 0.073434928
#> [31] 0.004742444 0.195112469 0.976898589 0.081027919 0.119890706 0.679963663
#> [37] 0.046225766 0.919522837 0.144912735 0.128185789 0.241059743 0.601971128
#> [43] 0.317970254 0.794166340 0.601971128 0.195112469 0.557957216 0.289122458
#> [49] 0.840280066 0.439891779 0.260302418 0.635173472 0.337982774 0.702678015
#> [55] 0.144912735 0.817162697 0.144912735 0.885286949 0.702678015 0.429400480
#> [61] 0.482267556 0.450433108 0.388126660 0.111732875 0.289122458 0.144912735
#> [67] 0.840280066 0.942460259 0.885286949 0.736581452 0.185971599 0.492982045
#> [73] 0.557957216 0.942460259 0.388126660 0.081027919 0.279298561 0.260302418
#> [79] 0.840280066 0.289122458 0.222428363 0.635173472 0.657373545 0.039441487
#> [85] 0.377906988 0.965353636 0.748092123 0.759620463 0.250680246 0.525188757
#> [91] 0.782581059 0.004742444 0.557957216 0.988437421 0.408564405 0.020436181
#> [97] 0.348164380 0.095969548 0.348164380 0.046225766 0.817162697 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 60 183 68 113 133 88 133.1 37 57 29 171 18 13
#> 13.15 9.24 20.62 22.86 14.65 18.37 14.65 12.52 14.46 15.45 16.57 15.21 14.34
#> 58 52 69 155 23 136 175 108 149 49 166 61 63
#> 19.34 10.42 23.23 13.08 16.92 21.83 21.91 18.29 8.37 12.19 19.98 10.12 22.77
#> 56 101 100 197 129 88.1 25 139 158 56.1 175.1 149.1 58.1
#> 12.21 9.97 16.07 21.60 23.41 18.37 6.32 21.49 20.14 12.21 21.91 8.37 19.34
#> 166.1 51 155.1 23.1 61.1 155.2 88.2 81 45 101.1 125 111 154
#> 19.98 18.23 13.08 16.92 10.12 13.08 18.37 14.06 17.42 9.97 15.65 17.45 12.63
#> 106 49.1 55 145 55.1 183.1 49.2 26 157 167 85 150 45.1
#> 16.67 12.19 19.34 10.07 19.34 9.24 12.19 15.77 15.10 15.55 16.44 20.33 17.42
#> 58.2 101.2 70 183.2 43 97 133.2 81.1 70.1 85.1 139.1 30 111.1
#> 19.34 9.97 7.38 9.24 12.10 19.14 14.65 14.06 7.38 16.44 21.49 17.43 17.45
#> 101.3 45.2 108.1 154.1 177 66 130 77 159 52.1 41 57.1 93
#> 9.97 17.42 18.29 12.63 12.53 22.13 16.47 7.27 10.55 10.42 18.02 14.46 10.33
#> 129.1 81.2 91 188 92 171.1 99 171.2 175.2 145.1 173 126 138
#> 23.41 14.06 5.33 16.16 22.92 16.57 21.19 16.57 21.91 10.07 24.00 24.00 24.00
#> 142 121 143 84 72 71 1 87 178 173.1 102 9 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 74 147 109 109.1 22 1.1 82 27 19 54 121.1 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 147.1 121.2 200 200.1 7.1 44 137 46 122 33 22.1 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20.1 94 186 11 75 162 138.1 148 142.1 151 17 9.1 31
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137.1 34 156 132 193 147.2 132.1 142.2 120 138.2 146 83.1 109.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146.1 87.1 132.2 11.1 22.2 174.1 28 131 33.1 80 142.3 46.1 75.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 156.1 53
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[25]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003352076 1.010300509 0.586437086
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.49855648 0.01353516 -0.19812527
#> grade_iii, Cure model
#> 0.61191620
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 88 18.37 1 47 0 0
#> 134 17.81 1 47 1 0
#> 36 21.19 1 48 0 1
#> 170 19.54 1 43 0 1
#> 167 15.55 1 56 1 0
#> 52 10.42 1 52 0 1
#> 189 10.51 1 NA 1 0
#> 88.1 18.37 1 47 0 0
#> 187 9.92 1 39 1 0
#> 133 14.65 1 57 0 0
#> 66 22.13 1 53 0 0
#> 68 20.62 1 44 0 0
#> 81 14.06 1 34 0 0
#> 130 16.47 1 53 0 1
#> 77 7.27 1 67 0 1
#> 177 12.53 1 75 0 0
#> 90 20.94 1 50 0 1
#> 29 15.45 1 68 1 0
#> 8 18.43 1 32 0 0
#> 100 16.07 1 60 0 0
#> 194 22.40 1 38 0 1
#> 99 21.19 1 38 0 1
#> 40 18.00 1 28 1 0
#> 45 17.42 1 54 0 1
#> 68.1 20.62 1 44 0 0
#> 164 23.60 1 76 0 1
#> 97 19.14 1 65 0 1
#> 32 20.90 1 37 1 0
#> 85 16.44 1 36 0 0
#> 114 13.68 1 NA 0 0
#> 188 16.16 1 46 0 1
#> 105 19.75 1 60 0 0
#> 175 21.91 1 43 0 0
#> 127 3.53 1 62 0 1
#> 51 18.23 1 83 0 1
#> 175.1 21.91 1 43 0 0
#> 192 16.44 1 31 1 0
#> 187.1 9.92 1 39 1 0
#> 117 17.46 1 26 0 1
#> 168 23.72 1 70 0 0
#> 166 19.98 1 48 0 0
#> 78 23.88 1 43 0 0
#> 60 13.15 1 38 1 0
#> 42 12.43 1 49 0 1
#> 154 12.63 1 20 1 0
#> 32.1 20.90 1 37 1 0
#> 168.1 23.72 1 70 0 0
#> 61 10.12 1 36 0 1
#> 117.1 17.46 1 26 0 1
#> 52.1 10.42 1 52 0 1
#> 36.1 21.19 1 48 0 1
#> 183 9.24 1 67 1 0
#> 199 19.81 1 NA 0 1
#> 125 15.65 1 67 1 0
#> 130.1 16.47 1 53 0 1
#> 39 15.59 1 37 0 1
#> 45.1 17.42 1 54 0 1
#> 41 18.02 1 40 1 0
#> 111 17.45 1 47 0 1
#> 153 21.33 1 55 1 0
#> 190 20.81 1 42 1 0
#> 79 16.23 1 54 1 0
#> 26 15.77 1 49 0 1
#> 78.1 23.88 1 43 0 0
#> 5 16.43 1 51 0 1
#> 181 16.46 1 45 0 1
#> 194.1 22.40 1 38 0 1
#> 154.1 12.63 1 20 1 0
#> 18 15.21 1 49 1 0
#> 155 13.08 1 26 0 0
#> 81.1 14.06 1 34 0 0
#> 133.1 14.65 1 57 0 0
#> 51.1 18.23 1 83 0 1
#> 90.1 20.94 1 50 0 1
#> 192.1 16.44 1 31 1 0
#> 56 12.21 1 60 0 0
#> 91 5.33 1 61 0 1
#> 18.1 15.21 1 49 1 0
#> 100.1 16.07 1 60 0 0
#> 169 22.41 1 46 0 0
#> 166.1 19.98 1 48 0 0
#> 166.2 19.98 1 48 0 0
#> 15 22.68 1 48 0 0
#> 86 23.81 1 58 0 1
#> 18.2 15.21 1 49 1 0
#> 45.2 17.42 1 54 0 1
#> 107 11.18 1 54 1 0
#> 169.1 22.41 1 46 0 0
#> 171 16.57 1 41 0 1
#> 184 17.77 1 38 0 0
#> 41.1 18.02 1 40 1 0
#> 81.2 14.06 1 34 0 0
#> 78.2 23.88 1 43 0 0
#> 29.1 15.45 1 68 1 0
#> 4 17.64 1 NA 0 1
#> 189.1 10.51 1 NA 1 0
#> 85.1 16.44 1 36 0 0
#> 190.1 20.81 1 42 1 0
#> 18.3 15.21 1 49 1 0
#> 24 23.89 1 38 0 0
#> 58 19.34 1 39 0 0
#> 55 19.34 1 69 0 1
#> 63 22.77 1 31 1 0
#> 169.2 22.41 1 46 0 0
#> 25 6.32 1 34 1 0
#> 184.1 17.77 1 38 0 0
#> 145 10.07 1 65 1 0
#> 99.1 21.19 1 38 0 1
#> 61.1 10.12 1 36 0 1
#> 15.1 22.68 1 48 0 0
#> 108 18.29 1 39 0 1
#> 57 14.46 1 45 0 1
#> 62 24.00 0 71 0 0
#> 75 24.00 0 21 1 0
#> 53 24.00 0 32 0 1
#> 152 24.00 0 36 0 1
#> 126 24.00 0 48 0 0
#> 165 24.00 0 47 0 0
#> 162 24.00 0 51 0 0
#> 53.1 24.00 0 32 0 1
#> 3 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 185 24.00 0 44 1 0
#> 98 24.00 0 34 1 0
#> 7 24.00 0 37 1 0
#> 65 24.00 0 57 1 0
#> 191 24.00 0 60 0 1
#> 138 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 46 24.00 0 71 0 0
#> 185.1 24.00 0 44 1 0
#> 115 24.00 0 NA 1 0
#> 162.1 24.00 0 51 0 0
#> 20 24.00 0 46 1 0
#> 87 24.00 0 27 0 0
#> 116 24.00 0 58 0 1
#> 7.1 24.00 0 37 1 0
#> 148 24.00 0 61 1 0
#> 132 24.00 0 55 0 0
#> 144 24.00 0 28 0 1
#> 20.1 24.00 0 46 1 0
#> 22 24.00 0 52 1 0
#> 148.1 24.00 0 61 1 0
#> 126.1 24.00 0 48 0 0
#> 35 24.00 0 51 0 0
#> 54 24.00 0 53 1 0
#> 112 24.00 0 61 0 0
#> 54.1 24.00 0 53 1 0
#> 122 24.00 0 66 0 0
#> 196 24.00 0 19 0 0
#> 95 24.00 0 68 0 1
#> 135 24.00 0 58 1 0
#> 151 24.00 0 42 0 0
#> 38 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 47 24.00 0 38 0 1
#> 148.2 24.00 0 61 1 0
#> 19 24.00 0 57 0 1
#> 74 24.00 0 43 0 1
#> 19.1 24.00 0 57 0 1
#> 71 24.00 0 51 0 0
#> 48 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 176 24.00 0 43 0 1
#> 83 24.00 0 6 0 0
#> 7.2 24.00 0 37 1 0
#> 3.1 24.00 0 31 1 0
#> 12 24.00 0 63 0 0
#> 132.1 24.00 0 55 0 0
#> 64 24.00 0 43 0 0
#> 73 24.00 0 NA 0 1
#> 144.1 24.00 0 28 0 1
#> 54.2 24.00 0 53 1 0
#> 200 24.00 0 64 0 0
#> 2 24.00 0 9 0 0
#> 112.1 24.00 0 61 0 0
#> 3.2 24.00 0 31 1 0
#> 80.1 24.00 0 41 0 0
#> 2.1 24.00 0 9 0 0
#> 27 24.00 0 63 1 0
#> 2.2 24.00 0 9 0 0
#> 137.1 24.00 0 45 1 0
#> 191.1 24.00 0 60 0 1
#> 146 24.00 0 63 1 0
#> 3.3 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 115.1 24.00 0 NA 1 0
#> 67.1 24.00 0 25 0 0
#> 98.1 24.00 0 34 1 0
#> 116.1 24.00 0 58 0 1
#> 102 24.00 0 49 0 0
#> 143 24.00 0 51 0 0
#> 11 24.00 0 42 0 1
#> 200.1 24.00 0 64 0 0
#> 137.2 24.00 0 45 1 0
#> 198 24.00 0 66 0 1
#> 75.1 24.00 0 21 1 0
#> 17 24.00 0 38 0 1
#> 131 24.00 0 66 0 0
#> 2.3 24.00 0 9 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.499 NA NA NA
#> 2 age, Cure model 0.0135 NA NA NA
#> 3 grade_ii, Cure model -0.198 NA NA NA
#> 4 grade_iii, Cure model 0.612 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00335 NA NA NA
#> 2 grade_ii, Survival model 1.01 NA NA NA
#> 3 grade_iii, Survival model 0.586 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.49856 0.01354 -0.19813 0.61192
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 263.6
#> Residual Deviance: 256.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.49855648 0.01353516 -0.19812527 0.61191620
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003352076 1.010300509 0.586437086
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.61131563 0.67431099 0.41337702 0.56883429 0.83561659 0.94417671
#> [7] 0.61131563 0.96813050 0.87312753 0.35875921 0.51582152 0.88872314
#> [13] 0.74351344 0.98196987 0.92436014 0.45716791 0.84134020 0.60293150
#> [19] 0.80600392 0.33075951 0.41337702 0.66692930 0.71680322 0.51582152
#> [25] 0.21783068 0.59453414 0.47843928 0.76301526 0.79997295 0.55995788
#> [31] 0.37293380 0.99553396 0.63612081 0.37293380 0.76301526 0.96813050
#> [37] 0.69581475 0.17573377 0.53365715 0.07900704 0.90415971 0.92935441
#> [43] 0.91438321 0.47843928 0.17573377 0.95383593 0.69581475 0.94417671
#> [49] 0.41337702 0.97738477 0.82394255 0.74351344 0.82980082 0.71680322
#> [55] 0.65191434 0.70983467 0.40042742 0.49788742 0.79389168 0.81798095
#> [61] 0.07900704 0.78770176 0.75653652 0.33075951 0.91438321 0.85238175
#> [67] 0.90927277 0.88872314 0.87312753 0.63612081 0.45716791 0.76301526
#> [73] 0.93431885 0.99104349 0.85238175 0.80600392 0.28578956 0.53365715
#> [79] 0.53365715 0.25412008 0.15164945 0.85238175 0.71680322 0.93927741
#> [85] 0.28578956 0.73683844 0.68151793 0.65191434 0.88872314 0.07900704
#> [91] 0.84134020 0.76301526 0.49788742 0.85238175 0.03275766 0.57756409
#> [97] 0.57756409 0.23738539 0.28578956 0.98652835 0.68151793 0.96339561
#> [103] 0.41337702 0.95383593 0.25412008 0.62789190 0.88353659 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 88 134 36 170 167 52 88.1 187 133 66 68 81 130
#> 18.37 17.81 21.19 19.54 15.55 10.42 18.37 9.92 14.65 22.13 20.62 14.06 16.47
#> 77 177 90 29 8 100 194 99 40 45 68.1 164 97
#> 7.27 12.53 20.94 15.45 18.43 16.07 22.40 21.19 18.00 17.42 20.62 23.60 19.14
#> 32 85 188 105 175 127 51 175.1 192 187.1 117 168 166
#> 20.90 16.44 16.16 19.75 21.91 3.53 18.23 21.91 16.44 9.92 17.46 23.72 19.98
#> 78 60 42 154 32.1 168.1 61 117.1 52.1 36.1 183 125 130.1
#> 23.88 13.15 12.43 12.63 20.90 23.72 10.12 17.46 10.42 21.19 9.24 15.65 16.47
#> 39 45.1 41 111 153 190 79 26 78.1 5 181 194.1 154.1
#> 15.59 17.42 18.02 17.45 21.33 20.81 16.23 15.77 23.88 16.43 16.46 22.40 12.63
#> 18 155 81.1 133.1 51.1 90.1 192.1 56 91 18.1 100.1 169 166.1
#> 15.21 13.08 14.06 14.65 18.23 20.94 16.44 12.21 5.33 15.21 16.07 22.41 19.98
#> 166.2 15 86 18.2 45.2 107 169.1 171 184 41.1 81.2 78.2 29.1
#> 19.98 22.68 23.81 15.21 17.42 11.18 22.41 16.57 17.77 18.02 14.06 23.88 15.45
#> 85.1 190.1 18.3 24 58 55 63 169.2 25 184.1 145 99.1 61.1
#> 16.44 20.81 15.21 23.89 19.34 19.34 22.77 22.41 6.32 17.77 10.07 21.19 10.12
#> 15.1 108 57 62 75 53 152 126 165 162 53.1 3 137
#> 22.68 18.29 14.46 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 98 7 65 191 138 80 46 185.1 162.1 20 87 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7.1 148 132 144 20.1 22 148.1 126.1 35 54 112 54.1 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 95 135 151 38 67 47 148.2 19 74 19.1 71 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 176 83 7.2 3.1 12 132.1 64 144.1 54.2 200 2 112.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.2 80.1 2.1 27 2.2 137.1 191.1 146 3.3 119 67.1 98.1 116.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 143 11 200.1 137.2 198 75.1 17 131 2.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[26]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00715874 0.71064468 0.58076983
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.52114956 0.02679942 0.30750013
#> grade_iii, Cure model
#> 1.16630158
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 23 16.92 1 61 0 0
#> 58 19.34 1 39 0 0
#> 136 21.83 1 43 0 1
#> 133 14.65 1 57 0 0
#> 179 18.63 1 42 0 0
#> 13 14.34 1 54 0 1
#> 61 10.12 1 36 0 1
#> 92 22.92 1 47 0 1
#> 69 23.23 1 25 0 1
#> 164 23.60 1 76 0 1
#> 10 10.53 1 34 0 0
#> 140 12.68 1 59 1 0
#> 145 10.07 1 65 1 0
#> 127 3.53 1 62 0 1
#> 88 18.37 1 47 0 0
#> 16 8.71 1 71 0 1
#> 157 15.10 1 47 0 0
#> 70 7.38 1 30 1 0
#> 55 19.34 1 69 0 1
#> 110 17.56 1 65 0 1
#> 111 17.45 1 47 0 1
#> 55.1 19.34 1 69 0 1
#> 57 14.46 1 45 0 1
#> 169 22.41 1 46 0 0
#> 88.1 18.37 1 47 0 0
#> 15 22.68 1 48 0 0
#> 13.1 14.34 1 54 0 1
#> 188 16.16 1 46 0 1
#> 39 15.59 1 37 0 1
#> 107 11.18 1 54 1 0
#> 190 20.81 1 42 1 0
#> 171 16.57 1 41 0 1
#> 24 23.89 1 38 0 0
#> 197 21.60 1 69 1 0
#> 159 10.55 1 50 0 1
#> 140.1 12.68 1 59 1 0
#> 145.1 10.07 1 65 1 0
#> 166 19.98 1 48 0 0
#> 57.1 14.46 1 45 0 1
#> 181 16.46 1 45 0 1
#> 39.1 15.59 1 37 0 1
#> 110.1 17.56 1 65 0 1
#> 101 9.97 1 10 0 1
#> 123 13.00 1 44 1 0
#> 15.1 22.68 1 48 0 0
#> 50 10.02 1 NA 1 0
#> 5 16.43 1 51 0 1
#> 5.1 16.43 1 51 0 1
#> 127.1 3.53 1 62 0 1
#> 51 18.23 1 83 0 1
#> 42 12.43 1 49 0 1
#> 106 16.67 1 49 1 0
#> 41 18.02 1 40 1 0
#> 179.1 18.63 1 42 0 0
#> 105 19.75 1 60 0 0
#> 197.1 21.60 1 69 1 0
#> 168 23.72 1 70 0 0
#> 190.1 20.81 1 42 1 0
#> 24.1 23.89 1 38 0 0
#> 175 21.91 1 43 0 0
#> 8 18.43 1 32 0 0
#> 117 17.46 1 26 0 1
#> 194 22.40 1 38 0 1
#> 197.2 21.60 1 69 1 0
#> 184 17.77 1 38 0 0
#> 42.1 12.43 1 49 0 1
#> 167 15.55 1 56 1 0
#> 164.1 23.60 1 76 0 1
#> 149 8.37 1 33 1 0
#> 32 20.90 1 37 1 0
#> 63 22.77 1 31 1 0
#> 45 17.42 1 54 0 1
#> 76 19.22 1 54 0 1
#> 179.2 18.63 1 42 0 0
#> 139 21.49 1 63 1 0
#> 100 16.07 1 60 0 0
#> 114 13.68 1 NA 0 0
#> 4 17.64 1 NA 0 1
#> 60 13.15 1 38 1 0
#> 192 16.44 1 31 1 0
#> 145.2 10.07 1 65 1 0
#> 79 16.23 1 54 1 0
#> 150 20.33 1 48 0 0
#> 63.1 22.77 1 31 1 0
#> 197.3 21.60 1 69 1 0
#> 106.1 16.67 1 49 1 0
#> 108 18.29 1 39 0 1
#> 108.1 18.29 1 39 0 1
#> 123.1 13.00 1 44 1 0
#> 90 20.94 1 50 0 1
#> 66 22.13 1 53 0 0
#> 114.1 13.68 1 NA 0 0
#> 59 10.16 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 15.2 22.68 1 48 0 0
#> 171.1 16.57 1 41 0 1
#> 66.1 22.13 1 53 0 0
#> 55.2 19.34 1 69 0 1
#> 192.1 16.44 1 31 1 0
#> 60.1 13.15 1 38 1 0
#> 41.1 18.02 1 40 1 0
#> 158 20.14 1 74 1 0
#> 168.1 23.72 1 70 0 0
#> 136.1 21.83 1 43 0 1
#> 86 23.81 1 58 0 1
#> 184.1 17.77 1 38 0 0
#> 6 15.64 1 39 0 0
#> 15.3 22.68 1 48 0 0
#> 153 21.33 1 55 1 0
#> 105.1 19.75 1 60 0 0
#> 36 21.19 1 48 0 1
#> 23.1 16.92 1 61 0 0
#> 112 24.00 0 61 0 0
#> 22 24.00 0 52 1 0
#> 142 24.00 0 53 0 0
#> 74 24.00 0 43 0 1
#> 72 24.00 0 40 0 1
#> 80 24.00 0 41 0 0
#> 44 24.00 0 56 0 0
#> 120 24.00 0 68 0 1
#> 137 24.00 0 45 1 0
#> 64 24.00 0 43 0 0
#> 1 24.00 0 23 1 0
#> 33 24.00 0 53 0 0
#> 138 24.00 0 44 1 0
#> 67 24.00 0 25 0 0
#> 185 24.00 0 44 1 0
#> 193 24.00 0 45 0 1
#> 71 24.00 0 51 0 0
#> 144 24.00 0 28 0 1
#> 62 24.00 0 71 0 0
#> 200 24.00 0 64 0 0
#> 46 24.00 0 71 0 0
#> 17 24.00 0 38 0 1
#> 87 24.00 0 27 0 0
#> 137.1 24.00 0 45 1 0
#> 28 24.00 0 67 1 0
#> 132 24.00 0 55 0 0
#> 126 24.00 0 48 0 0
#> 119 24.00 0 17 0 0
#> 147 24.00 0 76 1 0
#> 172 24.00 0 41 0 0
#> 151 24.00 0 42 0 0
#> 11 24.00 0 42 0 1
#> 109 24.00 0 48 0 0
#> 62.1 24.00 0 71 0 0
#> 67.1 24.00 0 25 0 0
#> 48 24.00 0 31 1 0
#> 186 24.00 0 45 1 0
#> 22.1 24.00 0 52 1 0
#> 135 24.00 0 58 1 0
#> 152 24.00 0 36 0 1
#> 137.2 24.00 0 45 1 0
#> 21 24.00 0 47 0 0
#> 53 24.00 0 32 0 1
#> 75 24.00 0 21 1 0
#> 71.1 24.00 0 51 0 0
#> 84 24.00 0 39 0 1
#> 162 24.00 0 51 0 0
#> 112.1 24.00 0 61 0 0
#> 75.1 24.00 0 21 1 0
#> 34 24.00 0 36 0 0
#> 104 24.00 0 50 1 0
#> 82 24.00 0 34 0 0
#> 80.1 24.00 0 41 0 0
#> 98 24.00 0 34 1 0
#> 11.1 24.00 0 42 0 1
#> 87.1 24.00 0 27 0 0
#> 151.1 24.00 0 42 0 0
#> 46.1 24.00 0 71 0 0
#> 21.1 24.00 0 47 0 0
#> 21.2 24.00 0 47 0 0
#> 67.2 24.00 0 25 0 0
#> 173 24.00 0 19 0 1
#> 94 24.00 0 51 0 1
#> 62.2 24.00 0 71 0 0
#> 132.1 24.00 0 55 0 0
#> 160 24.00 0 31 1 0
#> 84.1 24.00 0 39 0 1
#> 144.1 24.00 0 28 0 1
#> 200.1 24.00 0 64 0 0
#> 65 24.00 0 57 1 0
#> 185.1 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 138.1 24.00 0 44 1 0
#> 137.3 24.00 0 45 1 0
#> 141 24.00 0 44 1 0
#> 74.1 24.00 0 43 0 1
#> 104.1 24.00 0 50 1 0
#> 138.2 24.00 0 44 1 0
#> 28.1 24.00 0 67 1 0
#> 98.1 24.00 0 34 1 0
#> 138.3 24.00 0 44 1 0
#> 122 24.00 0 66 0 0
#> 173.1 24.00 0 19 0 1
#> 35 24.00 0 51 0 0
#> 104.2 24.00 0 50 1 0
#> 148 24.00 0 61 1 0
#> 83 24.00 0 6 0 0
#> 200.2 24.00 0 64 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.52 NA NA NA
#> 2 age, Cure model 0.0268 NA NA NA
#> 3 grade_ii, Cure model 0.308 NA NA NA
#> 4 grade_iii, Cure model 1.17 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00716 NA NA NA
#> 2 grade_ii, Survival model 0.711 NA NA NA
#> 3 grade_iii, Survival model 0.581 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.5211 0.0268 0.3075 1.1663
#>
#> Degrees of Freedom: 194 Total (i.e. Null); 191 Residual
#> Null Deviance: 268.5
#> Residual Deviance: 252.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.52114956 0.02679942 0.30750013 1.16630158
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00715874 0.71064468 0.58076983
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.602277579 0.387070665 0.214634824 0.781377597 0.433006171 0.807609536
#> [7] 0.917863322 0.093154644 0.081504270 0.058368539 0.909468479 0.859056489
#> [13] 0.926228989 0.983784081 0.470653110 0.959169077 0.772596023 0.975622612
#> [19] 0.387070665 0.555706048 0.583714568 0.387070665 0.790192364 0.161412312
#> [25] 0.470653110 0.123317197 0.807609536 0.719848161 0.746364584 0.892692718
#> [31] 0.322266426 0.639219999 0.006510961 0.235386067 0.901090343 0.859056489
#> [37] 0.926228989 0.359018332 0.790192364 0.666523285 0.746364584 0.555706048
#> [43] 0.950915739 0.842085354 0.123317197 0.693365971 0.693365971 0.983784081
#> [49] 0.508801957 0.875916349 0.620867766 0.518366089 0.433006171 0.368338737
#> [55] 0.235386067 0.035022036 0.322266426 0.006510961 0.203654823 0.461063578
#> [61] 0.574376340 0.172113565 0.235386067 0.536958740 0.875916349 0.763842875
#> [67] 0.058368539 0.967417079 0.312757154 0.104417491 0.593011640 0.423606022
#> [73] 0.433006171 0.273522326 0.728653458 0.824946586 0.675611251 0.926228989
#> [79] 0.711011962 0.340468460 0.104417491 0.235386067 0.620867766 0.489858182
#> [85] 0.489858182 0.842085354 0.303082696 0.182579722 0.657398601 0.123317197
#> [91] 0.639219999 0.182579722 0.387070665 0.675611251 0.824946586 0.518366089
#> [97] 0.349767772 0.035022036 0.214634824 0.024194280 0.536958740 0.737496069
#> [103] 0.123317197 0.283490933 0.368338737 0.293330570 0.602277579 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 23 58 136 133 179 13 61 92 69 164 10 140 145
#> 16.92 19.34 21.83 14.65 18.63 14.34 10.12 22.92 23.23 23.60 10.53 12.68 10.07
#> 127 88 16 157 70 55 110 111 55.1 57 169 88.1 15
#> 3.53 18.37 8.71 15.10 7.38 19.34 17.56 17.45 19.34 14.46 22.41 18.37 22.68
#> 13.1 188 39 107 190 171 24 197 159 140.1 145.1 166 57.1
#> 14.34 16.16 15.59 11.18 20.81 16.57 23.89 21.60 10.55 12.68 10.07 19.98 14.46
#> 181 39.1 110.1 101 123 15.1 5 5.1 127.1 51 42 106 41
#> 16.46 15.59 17.56 9.97 13.00 22.68 16.43 16.43 3.53 18.23 12.43 16.67 18.02
#> 179.1 105 197.1 168 190.1 24.1 175 8 117 194 197.2 184 42.1
#> 18.63 19.75 21.60 23.72 20.81 23.89 21.91 18.43 17.46 22.40 21.60 17.77 12.43
#> 167 164.1 149 32 63 45 76 179.2 139 100 60 192 145.2
#> 15.55 23.60 8.37 20.90 22.77 17.42 19.22 18.63 21.49 16.07 13.15 16.44 10.07
#> 79 150 63.1 197.3 106.1 108 108.1 123.1 90 66 130 15.2 171.1
#> 16.23 20.33 22.77 21.60 16.67 18.29 18.29 13.00 20.94 22.13 16.47 22.68 16.57
#> 66.1 55.2 192.1 60.1 41.1 158 168.1 136.1 86 184.1 6 15.3 153
#> 22.13 19.34 16.44 13.15 18.02 20.14 23.72 21.83 23.81 17.77 15.64 22.68 21.33
#> 105.1 36 23.1 112 22 142 74 72 80 44 120 137 64
#> 19.75 21.19 16.92 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 33 138 67 185 193 71 144 62 200 46 17 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137.1 28 132 126 119 147 172 151 11 109 62.1 67.1 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 22.1 135 152 137.2 21 53 75 71.1 84 162 112.1 75.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 104 82 80.1 98 11.1 87.1 151.1 46.1 21.1 21.2 67.2 173
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 62.2 132.1 160 84.1 144.1 200.1 65 185.1 31 138.1 137.3 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74.1 104.1 138.2 28.1 98.1 138.3 122 173.1 35 104.2 148 83 200.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[27]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0007902495 -0.1902875041 -0.2492456331
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.621392472 0.007669333 0.201672172
#> grade_iii, Cure model
#> 0.908253821
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 195 11.76 1 NA 1 0
#> 23 16.92 1 61 0 0
#> 127 3.53 1 62 0 1
#> 61 10.12 1 36 0 1
#> 93 10.33 1 52 0 1
#> 39 15.59 1 37 0 1
#> 187 9.92 1 39 1 0
#> 129 23.41 1 53 1 0
#> 32 20.90 1 37 1 0
#> 195.1 11.76 1 NA 1 0
#> 105 19.75 1 60 0 0
#> 81 14.06 1 34 0 0
#> 86 23.81 1 58 0 1
#> 61.1 10.12 1 36 0 1
#> 195.2 11.76 1 NA 1 0
#> 85 16.44 1 36 0 0
#> 184 17.77 1 38 0 0
#> 190 20.81 1 42 1 0
#> 125 15.65 1 67 1 0
#> 187.1 9.92 1 39 1 0
#> 194 22.40 1 38 0 1
#> 125.1 15.65 1 67 1 0
#> 68 20.62 1 44 0 0
#> 81.1 14.06 1 34 0 0
#> 133 14.65 1 57 0 0
#> 42 12.43 1 49 0 1
#> 56 12.21 1 60 0 0
#> 97 19.14 1 65 0 1
#> 51 18.23 1 83 0 1
#> 4 17.64 1 NA 0 1
#> 40 18.00 1 28 1 0
#> 36 21.19 1 48 0 1
#> 133.1 14.65 1 57 0 0
#> 189 10.51 1 NA 1 0
#> 199 19.81 1 NA 0 1
#> 40.1 18.00 1 28 1 0
#> 51.1 18.23 1 83 0 1
#> 97.1 19.14 1 65 0 1
#> 14 12.89 1 21 0 0
#> 51.2 18.23 1 83 0 1
#> 128 20.35 1 35 0 1
#> 197 21.60 1 69 1 0
#> 114 13.68 1 NA 0 0
#> 66 22.13 1 53 0 0
#> 158 20.14 1 74 1 0
#> 190.1 20.81 1 42 1 0
#> 4.1 17.64 1 NA 0 1
#> 39.1 15.59 1 37 0 1
#> 70 7.38 1 30 1 0
#> 197.1 21.60 1 69 1 0
#> 43 12.10 1 61 0 1
#> 4.2 17.64 1 NA 0 1
#> 41 18.02 1 40 1 0
#> 155 13.08 1 26 0 0
#> 127.1 3.53 1 62 0 1
#> 63 22.77 1 31 1 0
#> 77 7.27 1 67 0 1
#> 199.1 19.81 1 NA 0 1
#> 159 10.55 1 50 0 1
#> 56.1 12.21 1 60 0 0
#> 190.2 20.81 1 42 1 0
#> 63.1 22.77 1 31 1 0
#> 194.1 22.40 1 38 0 1
#> 36.1 21.19 1 48 0 1
#> 88 18.37 1 47 0 0
#> 13 14.34 1 54 0 1
#> 99 21.19 1 38 0 1
#> 195.3 11.76 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 169 22.41 1 46 0 0
#> 88.1 18.37 1 47 0 0
#> 171 16.57 1 41 0 1
#> 123 13.00 1 44 1 0
#> 85.1 16.44 1 36 0 0
#> 170 19.54 1 43 0 1
#> 194.2 22.40 1 38 0 1
#> 29 15.45 1 68 1 0
#> 108 18.29 1 39 0 1
#> 157 15.10 1 47 0 0
#> 194.3 22.40 1 38 0 1
#> 159.1 10.55 1 50 0 1
#> 108.1 18.29 1 39 0 1
#> 36.2 21.19 1 48 0 1
#> 199.2 19.81 1 NA 0 1
#> 16 8.71 1 71 0 1
#> 140 12.68 1 59 1 0
#> 159.2 10.55 1 50 0 1
#> 117 17.46 1 26 0 1
#> 85.2 16.44 1 36 0 0
#> 16.1 8.71 1 71 0 1
#> 5 16.43 1 51 0 1
#> 15 22.68 1 48 0 0
#> 40.2 18.00 1 28 1 0
#> 192 16.44 1 31 1 0
#> 107 11.18 1 54 1 0
#> 13.1 14.34 1 54 0 1
#> 114.1 13.68 1 NA 0 0
#> 41.1 18.02 1 40 1 0
#> 199.3 19.81 1 NA 0 1
#> 158.1 20.14 1 74 1 0
#> 184.1 17.77 1 38 0 0
#> 157.1 15.10 1 47 0 0
#> 164 23.60 1 76 0 1
#> 18 15.21 1 49 1 0
#> 149 8.37 1 33 1 0
#> 128.1 20.35 1 35 0 1
#> 37 12.52 1 57 1 0
#> 6 15.64 1 39 0 0
#> 10 10.53 1 34 0 0
#> 49 12.19 1 48 1 0
#> 125.2 15.65 1 67 1 0
#> 187.2 9.92 1 39 1 0
#> 82 24.00 0 34 0 0
#> 122 24.00 0 66 0 0
#> 71 24.00 0 51 0 0
#> 118 24.00 0 44 1 0
#> 121 24.00 0 57 1 0
#> 65 24.00 0 57 1 0
#> 19 24.00 0 57 0 1
#> 116 24.00 0 58 0 1
#> 22 24.00 0 52 1 0
#> 71.1 24.00 0 51 0 0
#> 35 24.00 0 51 0 0
#> 84 24.00 0 39 0 1
#> 137 24.00 0 45 1 0
#> 102 24.00 0 49 0 0
#> 95 24.00 0 68 0 1
#> 198 24.00 0 66 0 1
#> 132 24.00 0 55 0 0
#> 3 24.00 0 31 1 0
#> 2 24.00 0 9 0 0
#> 156 24.00 0 50 1 0
#> 196 24.00 0 19 0 0
#> 31 24.00 0 36 0 1
#> 22.1 24.00 0 52 1 0
#> 198.1 24.00 0 66 0 1
#> 46 24.00 0 71 0 0
#> 72 24.00 0 40 0 1
#> 21 24.00 0 47 0 0
#> 44 24.00 0 56 0 0
#> 120 24.00 0 68 0 1
#> 121.1 24.00 0 57 1 0
#> 72.1 24.00 0 40 0 1
#> 176 24.00 0 43 0 1
#> 94 24.00 0 51 0 1
#> 3.1 24.00 0 31 1 0
#> 22.2 24.00 0 52 1 0
#> 172 24.00 0 41 0 0
#> 47 24.00 0 38 0 1
#> 75 24.00 0 21 1 0
#> 21.1 24.00 0 47 0 0
#> 83 24.00 0 6 0 0
#> 141 24.00 0 44 1 0
#> 71.2 24.00 0 51 0 0
#> 104 24.00 0 50 1 0
#> 141.1 24.00 0 44 1 0
#> 82.1 24.00 0 34 0 0
#> 82.2 24.00 0 34 0 0
#> 20 24.00 0 46 1 0
#> 144 24.00 0 28 0 1
#> 174 24.00 0 49 1 0
#> 174.1 24.00 0 49 1 0
#> 152 24.00 0 36 0 1
#> 80 24.00 0 41 0 0
#> 71.3 24.00 0 51 0 0
#> 185 24.00 0 44 1 0
#> 72.2 24.00 0 40 0 1
#> 109 24.00 0 48 0 0
#> 75.1 24.00 0 21 1 0
#> 21.2 24.00 0 47 0 0
#> 3.2 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 9 24.00 0 31 1 0
#> 182 24.00 0 35 0 0
#> 46.1 24.00 0 71 0 0
#> 28 24.00 0 67 1 0
#> 104.1 24.00 0 50 1 0
#> 31.1 24.00 0 36 0 1
#> 104.2 24.00 0 50 1 0
#> 172.1 24.00 0 41 0 0
#> 148 24.00 0 61 1 0
#> 146 24.00 0 63 1 0
#> 132.1 24.00 0 55 0 0
#> 186 24.00 0 45 1 0
#> 162 24.00 0 51 0 0
#> 138 24.00 0 44 1 0
#> 151 24.00 0 42 0 0
#> 38 24.00 0 31 1 0
#> 116.1 24.00 0 58 0 1
#> 21.3 24.00 0 47 0 0
#> 11 24.00 0 42 0 1
#> 109.1 24.00 0 48 0 0
#> 27 24.00 0 63 1 0
#> 12 24.00 0 63 0 0
#> 11.1 24.00 0 42 0 1
#> 9.1 24.00 0 31 1 0
#> 162.1 24.00 0 51 0 0
#> 38.1 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 147 24.00 0 76 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.621 NA NA NA
#> 2 age, Cure model 0.00767 NA NA NA
#> 3 grade_ii, Cure model 0.202 NA NA NA
#> 4 grade_iii, Cure model 0.908 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000790 NA NA NA
#> 2 grade_ii, Survival model -0.190 NA NA NA
#> 3 grade_iii, Survival model -0.249 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.621392 0.007669 0.201672 0.908254
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 257.3
#> Residual Deviance: 249.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.621392472 0.007669333 0.201672172 0.908253821
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0007902495 -0.1902875041 -0.2492456331
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.403580574 0.975403892 0.854669989 0.842730055 0.532857802 0.878543697
#> [7] 0.012571836 0.130852800 0.212073475 0.645371541 0.001668344 0.854669989
#> [13] 0.435974174 0.371860148 0.139767926 0.489097353 0.878543697 0.047700931
#> [19] 0.489097353 0.165789040 0.645371541 0.600163017 0.725721478 0.737356545
#> [25] 0.231395356 0.290157126 0.340853385 0.099057482 0.600163017 0.340853385
#> [31] 0.290157126 0.231395356 0.691074267 0.290157126 0.174978284 0.083068967
#> [37] 0.075007590 0.193329421 0.139767926 0.532857802 0.950852518 0.083068967
#> [43] 0.772162477 0.320221469 0.668100992 0.975403892 0.019526005 0.963107801
#> [49] 0.795662070 0.737356545 0.139767926 0.019526005 0.047700931 0.099057482
#> [55] 0.250828802 0.622663372 0.099057482 0.425106940 0.040160570 0.250828802
#> [61] 0.414309435 0.679568063 0.435974174 0.221682469 0.047700931 0.555092691
#> [67] 0.270318033 0.577699848 0.047700931 0.795662070 0.270318033 0.099057482
#> [73] 0.914397957 0.702583628 0.795662070 0.392865135 0.435974174 0.914397957
#> [79] 0.478128385 0.032674388 0.340853385 0.435974174 0.783893972 0.622663372
#> [85] 0.320221469 0.193329421 0.371860148 0.577699848 0.006392117 0.566373179
#> [91] 0.938627591 0.174978284 0.714132902 0.521735968 0.830832598 0.760476664
#> [97] 0.489097353 0.878543697 0.000000000 0.000000000 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 23 127 61 93 39 187 129 32 105 81 86 61.1 85
#> 16.92 3.53 10.12 10.33 15.59 9.92 23.41 20.90 19.75 14.06 23.81 10.12 16.44
#> 184 190 125 187.1 194 125.1 68 81.1 133 42 56 97 51
#> 17.77 20.81 15.65 9.92 22.40 15.65 20.62 14.06 14.65 12.43 12.21 19.14 18.23
#> 40 36 133.1 40.1 51.1 97.1 14 51.2 128 197 66 158 190.1
#> 18.00 21.19 14.65 18.00 18.23 19.14 12.89 18.23 20.35 21.60 22.13 20.14 20.81
#> 39.1 70 197.1 43 41 155 127.1 63 77 159 56.1 190.2 63.1
#> 15.59 7.38 21.60 12.10 18.02 13.08 3.53 22.77 7.27 10.55 12.21 20.81 22.77
#> 194.1 36.1 88 13 99 130 169 88.1 171 123 85.1 170 194.2
#> 22.40 21.19 18.37 14.34 21.19 16.47 22.41 18.37 16.57 13.00 16.44 19.54 22.40
#> 29 108 157 194.3 159.1 108.1 36.2 16 140 159.2 117 85.2 16.1
#> 15.45 18.29 15.10 22.40 10.55 18.29 21.19 8.71 12.68 10.55 17.46 16.44 8.71
#> 5 15 40.2 192 107 13.1 41.1 158.1 184.1 157.1 164 18 149
#> 16.43 22.68 18.00 16.44 11.18 14.34 18.02 20.14 17.77 15.10 23.60 15.21 8.37
#> 128.1 37 6 10 49 125.2 187.2 82 122 71 118 121 65
#> 20.35 12.52 15.64 10.53 12.19 15.65 9.92 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 116 22 71.1 35 84 137 102 95 198 132 3 2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 196 31 22.1 198.1 46 72 21 44 120 121.1 72.1 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 3.1 22.2 172 47 75 21.1 83 141 71.2 104 141.1 82.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82.2 20 144 174 174.1 152 80 71.3 185 72.2 109 75.1 21.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.2 67 9 182 46.1 28 104.1 31.1 104.2 172.1 148 146 132.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 162 138 151 38 116.1 21.3 11 109.1 27 12 11.1 9.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162.1 38.1 193 147
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[28]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.002393253 0.110128592 -0.003803464
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.69977547 0.01232235 0.46131719
#> grade_iii, Cure model
#> 0.55055196
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 18 15.21 1 49 1 0
#> 63 22.77 1 31 1 0
#> 36 21.19 1 48 0 1
#> 88 18.37 1 47 0 0
#> 30 17.43 1 78 0 0
#> 175 21.91 1 43 0 0
#> 113 22.86 1 34 0 0
#> 50 10.02 1 NA 1 0
#> 81 14.06 1 34 0 0
#> 50.1 10.02 1 NA 1 0
#> 106 16.67 1 49 1 0
#> 41 18.02 1 40 1 0
#> 197 21.60 1 69 1 0
#> 192 16.44 1 31 1 0
#> 108 18.29 1 39 0 1
#> 37 12.52 1 57 1 0
#> 100 16.07 1 60 0 0
#> 91 5.33 1 61 0 1
#> 6 15.64 1 39 0 0
#> 6.1 15.64 1 39 0 0
#> 124 9.73 1 NA 1 0
#> 199 19.81 1 NA 0 1
#> 149 8.37 1 33 1 0
#> 133 14.65 1 57 0 0
#> 124.1 9.73 1 NA 1 0
#> 175.1 21.91 1 43 0 0
#> 155 13.08 1 26 0 0
#> 30.1 17.43 1 78 0 0
#> 105 19.75 1 60 0 0
#> 123 13.00 1 44 1 0
#> 45 17.42 1 54 0 1
#> 100.1 16.07 1 60 0 0
#> 63.1 22.77 1 31 1 0
#> 86 23.81 1 58 0 1
#> 99 21.19 1 38 0 1
#> 63.2 22.77 1 31 1 0
#> 10 10.53 1 34 0 0
#> 192.1 16.44 1 31 1 0
#> 155.1 13.08 1 26 0 0
#> 39 15.59 1 37 0 1
#> 130 16.47 1 53 0 1
#> 105.1 19.75 1 60 0 0
#> 128 20.35 1 35 0 1
#> 199.1 19.81 1 NA 0 1
#> 140 12.68 1 59 1 0
#> 187 9.92 1 39 1 0
#> 175.2 21.91 1 43 0 0
#> 85 16.44 1 36 0 0
#> 130.1 16.47 1 53 0 1
#> 89 11.44 1 NA 0 0
#> 68 20.62 1 44 0 0
#> 158 20.14 1 74 1 0
#> 42 12.43 1 49 0 1
#> 56 12.21 1 60 0 0
#> 66 22.13 1 53 0 0
#> 59 10.16 1 NA 1 0
#> 56.1 12.21 1 60 0 0
#> 36.1 21.19 1 48 0 1
#> 99.1 21.19 1 38 0 1
#> 92 22.92 1 47 0 1
#> 145 10.07 1 65 1 0
#> 78 23.88 1 43 0 0
#> 153 21.33 1 55 1 0
#> 164 23.60 1 76 0 1
#> 194 22.40 1 38 0 1
#> 5 16.43 1 51 0 1
#> 197.1 21.60 1 69 1 0
#> 166 19.98 1 48 0 0
#> 97 19.14 1 65 0 1
#> 56.2 12.21 1 60 0 0
#> 15 22.68 1 48 0 0
#> 55 19.34 1 69 0 1
#> 123.1 13.00 1 44 1 0
#> 192.2 16.44 1 31 1 0
#> 52 10.42 1 52 0 1
#> 29 15.45 1 68 1 0
#> 81.1 14.06 1 34 0 0
#> 117 17.46 1 26 0 1
#> 129 23.41 1 53 1 0
#> 52.1 10.42 1 52 0 1
#> 179 18.63 1 42 0 0
#> 106.1 16.67 1 49 1 0
#> 187.1 9.92 1 39 1 0
#> 110 17.56 1 65 0 1
#> 106.2 16.67 1 49 1 0
#> 180 14.82 1 37 0 0
#> 79 16.23 1 54 1 0
#> 61 10.12 1 36 0 1
#> 140.1 12.68 1 59 1 0
#> 190 20.81 1 42 1 0
#> 195 11.76 1 NA 1 0
#> 99.2 21.19 1 38 0 1
#> 154 12.63 1 20 1 0
#> 169 22.41 1 46 0 0
#> 177 12.53 1 75 0 0
#> 18.1 15.21 1 49 1 0
#> 26 15.77 1 49 0 1
#> 76 19.22 1 54 0 1
#> 43 12.10 1 61 0 1
#> 100.2 16.07 1 60 0 0
#> 167 15.55 1 56 1 0
#> 26.1 15.77 1 49 0 1
#> 113.1 22.86 1 34 0 0
#> 154.1 12.63 1 20 1 0
#> 88.1 18.37 1 47 0 0
#> 16 8.71 1 71 0 1
#> 96 14.54 1 33 0 1
#> 145.1 10.07 1 65 1 0
#> 155.2 13.08 1 26 0 0
#> 63.3 22.77 1 31 1 0
#> 129.1 23.41 1 53 1 0
#> 166.1 19.98 1 48 0 0
#> 178 24.00 0 52 1 0
#> 95 24.00 0 68 0 1
#> 109 24.00 0 48 0 0
#> 67 24.00 0 25 0 0
#> 34 24.00 0 36 0 0
#> 7 24.00 0 37 1 0
#> 35 24.00 0 51 0 0
#> 119 24.00 0 17 0 0
#> 102 24.00 0 49 0 0
#> 94 24.00 0 51 0 1
#> 151 24.00 0 42 0 0
#> 142 24.00 0 53 0 0
#> 112 24.00 0 61 0 0
#> 67.1 24.00 0 25 0 0
#> 53 24.00 0 32 0 1
#> 62 24.00 0 71 0 0
#> 12 24.00 0 63 0 0
#> 193 24.00 0 45 0 1
#> 176 24.00 0 43 0 1
#> 87 24.00 0 27 0 0
#> 131 24.00 0 66 0 0
#> 165 24.00 0 47 0 0
#> 148 24.00 0 61 1 0
#> 162 24.00 0 51 0 0
#> 162.1 24.00 0 51 0 0
#> 185 24.00 0 44 1 0
#> 119.1 24.00 0 17 0 0
#> 185.1 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 53.1 24.00 0 32 0 1
#> 64 24.00 0 43 0 0
#> 103 24.00 0 56 1 0
#> 22 24.00 0 52 1 0
#> 152 24.00 0 36 0 1
#> 94.1 24.00 0 51 0 1
#> 7.1 24.00 0 37 1 0
#> 121 24.00 0 57 1 0
#> 132 24.00 0 55 0 0
#> 143 24.00 0 51 0 0
#> 186 24.00 0 45 1 0
#> 174 24.00 0 49 1 0
#> 143.1 24.00 0 51 0 0
#> 62.1 24.00 0 71 0 0
#> 198 24.00 0 66 0 1
#> 19 24.00 0 57 0 1
#> 80 24.00 0 41 0 0
#> 193.1 24.00 0 45 0 1
#> 148.1 24.00 0 61 1 0
#> 19.1 24.00 0 57 0 1
#> 126 24.00 0 48 0 0
#> 126.1 24.00 0 48 0 0
#> 135 24.00 0 58 1 0
#> 196 24.00 0 19 0 0
#> 72 24.00 0 40 0 1
#> 132.1 24.00 0 55 0 0
#> 143.2 24.00 0 51 0 0
#> 9 24.00 0 31 1 0
#> 182 24.00 0 35 0 0
#> 138 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 138.1 24.00 0 44 1 0
#> 21 24.00 0 47 0 0
#> 21.1 24.00 0 47 0 0
#> 126.2 24.00 0 48 0 0
#> 7.2 24.00 0 37 1 0
#> 53.2 24.00 0 32 0 1
#> 44 24.00 0 56 0 0
#> 82 24.00 0 34 0 0
#> 144 24.00 0 28 0 1
#> 9.1 24.00 0 31 1 0
#> 163 24.00 0 66 0 0
#> 44.1 24.00 0 56 0 0
#> 137 24.00 0 45 1 0
#> 172 24.00 0 41 0 0
#> 47 24.00 0 38 0 1
#> 138.2 24.00 0 44 1 0
#> 17 24.00 0 38 0 1
#> 147 24.00 0 76 1 0
#> 53.3 24.00 0 32 0 1
#> 2 24.00 0 9 0 0
#> 198.1 24.00 0 66 0 1
#> 11 24.00 0 42 0 1
#> 141 24.00 0 44 1 0
#> 3 24.00 0 31 1 0
#> 182.1 24.00 0 35 0 0
#> 98 24.00 0 34 1 0
#> 87.1 24.00 0 27 0 0
#> 62.2 24.00 0 71 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.700 NA NA NA
#> 2 age, Cure model 0.0123 NA NA NA
#> 3 grade_ii, Cure model 0.461 NA NA NA
#> 4 grade_iii, Cure model 0.551 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00239 NA NA NA
#> 2 grade_ii, Survival model 0.110 NA NA NA
#> 3 grade_iii, Survival model -0.00380 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.69978 0.01232 0.46132 0.55055
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 257.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.69977547 0.01232235 0.46131719 0.55055196
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.002393253 0.110128592 -0.003803464
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.71110315 0.12569385 0.27427093 0.43903689 0.49590468 0.21197871
#> [7] 0.10129429 0.75470431 0.52384039 0.46749250 0.24315132 0.56924386
#> [13] 0.45795323 0.85758428 0.62273847 0.99170311 0.66690766 0.66690766
#> [19] 0.98339560 0.73725249 0.21197871 0.77201367 0.49590468 0.38116770
#> [25] 0.79777640 0.51448671 0.62273847 0.12569385 0.03023304 0.27427093
#> [31] 0.12569385 0.90818819 0.56924386 0.77201367 0.68456783 0.55103837
#> [37] 0.38116770 0.34187569 0.81495596 0.95847470 0.21197871 0.56924386
#> [43] 0.55103837 0.33185868 0.35186834 0.86609524 0.87459617 0.20084860
#> [49] 0.87459617 0.27427093 0.27427093 0.08798222 0.94181084 0.01226472
#> [55] 0.26383312 0.04712487 0.18963463 0.60468465 0.24315132 0.36176748
#> [61] 0.41978992 0.87459617 0.16700242 0.40041687 0.79777640 0.56924386
#> [67] 0.91662992 0.70229170 0.75470431 0.48645161 0.06298117 0.91662992
#> [73] 0.42942480 0.52384039 0.95847470 0.47698749 0.52384039 0.72850746
#> [79] 0.61372951 0.93339622 0.81495596 0.32180801 0.27427093 0.83203268
#> [85] 0.17836017 0.84904964 0.71110315 0.64920164 0.41011868 0.89973981
#> [91] 0.62273847 0.69344542 0.64920164 0.10129429 0.83203268 0.43903689
#> [97] 0.97507345 0.74598239 0.94181084 0.77201367 0.12569385 0.06298117
#> [103] 0.36176748 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 18 63 36 88 30 175 113 81 106 41 197 192 108
#> 15.21 22.77 21.19 18.37 17.43 21.91 22.86 14.06 16.67 18.02 21.60 16.44 18.29
#> 37 100 91 6 6.1 149 133 175.1 155 30.1 105 123 45
#> 12.52 16.07 5.33 15.64 15.64 8.37 14.65 21.91 13.08 17.43 19.75 13.00 17.42
#> 100.1 63.1 86 99 63.2 10 192.1 155.1 39 130 105.1 128 140
#> 16.07 22.77 23.81 21.19 22.77 10.53 16.44 13.08 15.59 16.47 19.75 20.35 12.68
#> 187 175.2 85 130.1 68 158 42 56 66 56.1 36.1 99.1 92
#> 9.92 21.91 16.44 16.47 20.62 20.14 12.43 12.21 22.13 12.21 21.19 21.19 22.92
#> 145 78 153 164 194 5 197.1 166 97 56.2 15 55 123.1
#> 10.07 23.88 21.33 23.60 22.40 16.43 21.60 19.98 19.14 12.21 22.68 19.34 13.00
#> 192.2 52 29 81.1 117 129 52.1 179 106.1 187.1 110 106.2 180
#> 16.44 10.42 15.45 14.06 17.46 23.41 10.42 18.63 16.67 9.92 17.56 16.67 14.82
#> 79 61 140.1 190 99.2 154 169 177 18.1 26 76 43 100.2
#> 16.23 10.12 12.68 20.81 21.19 12.63 22.41 12.53 15.21 15.77 19.22 12.10 16.07
#> 167 26.1 113.1 154.1 88.1 16 96 145.1 155.2 63.3 129.1 166.1 178
#> 15.55 15.77 22.86 12.63 18.37 8.71 14.54 10.07 13.08 22.77 23.41 19.98 24.00
#> 95 109 67 34 7 35 119 102 94 151 142 112 67.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 62 12 193 176 87 131 165 148 162 162.1 185 119.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185.1 53.1 64 103 22 152 94.1 7.1 121 132 143 186 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143.1 62.1 198 19 80 193.1 148.1 19.1 126 126.1 135 196 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.1 143.2 9 182 138 65 138.1 21 21.1 126.2 7.2 53.2 44
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82 144 9.1 163 44.1 137 172 47 138.2 17 147 53.3 2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198.1 11 141 3 182.1 98 87.1 62.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[29]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.009519455 0.554220663 0.218504384
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.04506499 0.02022294 0.02003676
#> grade_iii, Cure model
#> 0.84805620
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 128 20.35 1 35 0 1
#> 25 6.32 1 34 1 0
#> 92 22.92 1 47 0 1
#> 145 10.07 1 65 1 0
#> 136 21.83 1 43 0 1
#> 140 12.68 1 59 1 0
#> 25.1 6.32 1 34 1 0
#> 42 12.43 1 49 0 1
#> 88 18.37 1 47 0 0
#> 93 10.33 1 52 0 1
#> 8 18.43 1 32 0 0
#> 169 22.41 1 46 0 0
#> 81 14.06 1 34 0 0
#> 32 20.90 1 37 1 0
#> 130 16.47 1 53 0 1
#> 106 16.67 1 49 1 0
#> 129 23.41 1 53 1 0
#> 167 15.55 1 56 1 0
#> 159 10.55 1 50 0 1
#> 55 19.34 1 69 0 1
#> 99 21.19 1 38 0 1
#> 124 9.73 1 NA 1 0
#> 32.1 20.90 1 37 1 0
#> 69 23.23 1 25 0 1
#> 4 17.64 1 NA 0 1
#> 55.1 19.34 1 69 0 1
#> 10 10.53 1 34 0 0
#> 183 9.24 1 67 1 0
#> 124.1 9.73 1 NA 1 0
#> 154 12.63 1 20 1 0
#> 89 11.44 1 NA 0 0
#> 179 18.63 1 42 0 0
#> 167.1 15.55 1 56 1 0
#> 85 16.44 1 36 0 0
#> 93.1 10.33 1 52 0 1
#> 51 18.23 1 83 0 1
#> 24 23.89 1 38 0 0
#> 66 22.13 1 53 0 0
#> 123 13.00 1 44 1 0
#> 164 23.60 1 76 0 1
#> 76 19.22 1 54 0 1
#> 16 8.71 1 71 0 1
#> 157 15.10 1 47 0 0
#> 181 16.46 1 45 0 1
#> 164.1 23.60 1 76 0 1
#> 168 23.72 1 70 0 0
#> 171 16.57 1 41 0 1
#> 134 17.81 1 47 1 0
#> 56 12.21 1 60 0 0
#> 170 19.54 1 43 0 1
#> 129.1 23.41 1 53 1 0
#> 179.1 18.63 1 42 0 0
#> 124.2 9.73 1 NA 1 0
#> 13 14.34 1 54 0 1
#> 181.1 16.46 1 45 0 1
#> 145.1 10.07 1 65 1 0
#> 77 7.27 1 67 0 1
#> 167.2 15.55 1 56 1 0
#> 10.1 10.53 1 34 0 0
#> 183.1 9.24 1 67 1 0
#> 93.2 10.33 1 52 0 1
#> 106.1 16.67 1 49 1 0
#> 158 20.14 1 74 1 0
#> 25.2 6.32 1 34 1 0
#> 10.2 10.53 1 34 0 0
#> 30 17.43 1 78 0 0
#> 164.2 23.60 1 76 0 1
#> 29 15.45 1 68 1 0
#> 36 21.19 1 48 0 1
#> 14 12.89 1 21 0 0
#> 68 20.62 1 44 0 0
#> 127 3.53 1 62 0 1
#> 56.1 12.21 1 60 0 0
#> 13.1 14.34 1 54 0 1
#> 24.1 23.89 1 38 0 0
#> 16.1 8.71 1 71 0 1
#> 36.1 21.19 1 48 0 1
#> 134.1 17.81 1 47 1 0
#> 180 14.82 1 37 0 0
#> 197 21.60 1 69 1 0
#> 194 22.40 1 38 0 1
#> 5 16.43 1 51 0 1
#> 113 22.86 1 34 0 0
#> 150 20.33 1 48 0 0
#> 14.1 12.89 1 21 0 0
#> 171.1 16.57 1 41 0 1
#> 25.3 6.32 1 34 1 0
#> 139 21.49 1 63 1 0
#> 14.2 12.89 1 21 0 0
#> 92.1 22.92 1 47 0 1
#> 153 21.33 1 55 1 0
#> 194.1 22.40 1 38 0 1
#> 154.1 12.63 1 20 1 0
#> 128.1 20.35 1 35 0 1
#> 89.1 11.44 1 NA 0 0
#> 117 17.46 1 26 0 1
#> 23 16.92 1 61 0 0
#> 66.1 22.13 1 53 0 0
#> 5.1 16.43 1 51 0 1
#> 159.1 10.55 1 50 0 1
#> 124.3 9.73 1 NA 1 0
#> 39 15.59 1 37 0 1
#> 8.1 18.43 1 32 0 0
#> 59 10.16 1 NA 1 0
#> 169.1 22.41 1 46 0 0
#> 105 19.75 1 60 0 0
#> 133 14.65 1 57 0 0
#> 190 20.81 1 42 1 0
#> 52 10.42 1 52 0 1
#> 70 7.38 1 30 1 0
#> 108 18.29 1 39 0 1
#> 39.1 15.59 1 37 0 1
#> 34 24.00 0 36 0 0
#> 82 24.00 0 34 0 0
#> 119 24.00 0 17 0 0
#> 7 24.00 0 37 1 0
#> 11 24.00 0 42 0 1
#> 109 24.00 0 48 0 0
#> 3 24.00 0 31 1 0
#> 132 24.00 0 55 0 0
#> 9 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 103 24.00 0 56 1 0
#> 53 24.00 0 32 0 1
#> 119.1 24.00 0 17 0 0
#> 178 24.00 0 52 1 0
#> 84 24.00 0 39 0 1
#> 31 24.00 0 36 0 1
#> 1 24.00 0 23 1 0
#> 1.1 24.00 0 23 1 0
#> 185 24.00 0 44 1 0
#> 138 24.00 0 44 1 0
#> 38 24.00 0 31 1 0
#> 103.1 24.00 0 56 1 0
#> 33 24.00 0 53 0 0
#> 162 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 80 24.00 0 41 0 0
#> 116 24.00 0 58 0 1
#> 94 24.00 0 51 0 1
#> 12 24.00 0 63 0 0
#> 160 24.00 0 31 1 0
#> 141 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 144 24.00 0 28 0 1
#> 47 24.00 0 38 0 1
#> 135 24.00 0 58 1 0
#> 11.1 24.00 0 42 0 1
#> 35 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 80.1 24.00 0 41 0 0
#> 118 24.00 0 44 1 0
#> 103.2 24.00 0 56 1 0
#> 182 24.00 0 35 0 0
#> 98 24.00 0 34 1 0
#> 64 24.00 0 43 0 0
#> 34.1 24.00 0 36 0 0
#> 121 24.00 0 57 1 0
#> 148 24.00 0 61 1 0
#> 146.1 24.00 0 63 1 0
#> 2 24.00 0 9 0 0
#> 122 24.00 0 66 0 0
#> 35.1 24.00 0 51 0 0
#> 135.1 24.00 0 58 1 0
#> 142 24.00 0 53 0 0
#> 80.2 24.00 0 41 0 0
#> 47.1 24.00 0 38 0 1
#> 176 24.00 0 43 0 1
#> 163 24.00 0 66 0 0
#> 74 24.00 0 43 0 1
#> 54 24.00 0 53 1 0
#> 185.1 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 200 24.00 0 64 0 0
#> 83 24.00 0 6 0 0
#> 95 24.00 0 68 0 1
#> 84.1 24.00 0 39 0 1
#> 182.1 24.00 0 35 0 0
#> 12.1 24.00 0 63 0 0
#> 31.1 24.00 0 36 0 1
#> 126 24.00 0 48 0 0
#> 109.1 24.00 0 48 0 0
#> 174 24.00 0 49 1 0
#> 160.1 24.00 0 31 1 0
#> 11.2 24.00 0 42 0 1
#> 162.1 24.00 0 51 0 0
#> 48 24.00 0 31 1 0
#> 138.1 24.00 0 44 1 0
#> 94.1 24.00 0 51 0 1
#> 82.1 24.00 0 34 0 0
#> 131 24.00 0 66 0 0
#> 172 24.00 0 41 0 0
#> 34.2 24.00 0 36 0 0
#> 11.3 24.00 0 42 0 1
#> 48.1 24.00 0 31 1 0
#> 74.1 24.00 0 43 0 1
#> 64.1 24.00 0 43 0 0
#> 33.1 24.00 0 53 0 0
#> 35.2 24.00 0 51 0 0
#> 102 24.00 0 49 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.05 NA NA NA
#> 2 age, Cure model 0.0202 NA NA NA
#> 3 grade_ii, Cure model 0.0200 NA NA NA
#> 4 grade_iii, Cure model 0.848 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00952 NA NA NA
#> 2 grade_ii, Survival model 0.554 NA NA NA
#> 3 grade_iii, Survival model 0.219 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.04506 0.02022 0.02004 0.84806
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.8
#> Residual Deviance: 253.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.04506499 0.02022294 0.02003676 0.84805620
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.009519455 0.554220663 0.218504384
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.211685302 0.943634470 0.049999012 0.852006347 0.117560022 0.685726591
#> [7] 0.943634470 0.718419065 0.331246498 0.818184139 0.311933955 0.070816427
#> [13] 0.631143759 0.177446819 0.451827392 0.411330676 0.030607122 0.535285520
#> [19] 0.751352796 0.265035078 0.152147295 0.177446819 0.043160991 0.265035078
#> [25] 0.773496109 0.874744262 0.696782165 0.292930641 0.535285520 0.482780327
#> [31] 0.818184139 0.351101505 0.001922832 0.101198598 0.642133255 0.013655527
#> [37] 0.283475410 0.897529701 0.577159005 0.462164521 0.013655527 0.008081871
#> [43] 0.431503972 0.361173740 0.729356669 0.255879096 0.030607122 0.292930641
#> [49] 0.609459605 0.462164521 0.852006347 0.932057455 0.535285520 0.773496109
#> [55] 0.874744262 0.818184139 0.411330676 0.237824030 0.943634470 0.773496109
#> [61] 0.390924840 0.013655527 0.566529197 0.152147295 0.653095561 0.202966454
#> [67] 0.988536844 0.729356669 0.609459605 0.001922832 0.897529701 0.152147295
#> [73] 0.361173740 0.587859908 0.126155116 0.085825057 0.493266363 0.063457422
#> [79] 0.228915179 0.653095561 0.431503972 0.943634470 0.134807915 0.653095561
#> [85] 0.049999012 0.143485675 0.085825057 0.696782165 0.211685302 0.380915244
#> [91] 0.401070591 0.101198598 0.493266363 0.751352796 0.514222171 0.311933955
#> [97] 0.070816427 0.246779708 0.598618958 0.194373952 0.806865738 0.920529481
#> [103] 0.341153531 0.514222171 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 128 25 92 145 136 140 25.1 42 88 93 8 169 81
#> 20.35 6.32 22.92 10.07 21.83 12.68 6.32 12.43 18.37 10.33 18.43 22.41 14.06
#> 32 130 106 129 167 159 55 99 32.1 69 55.1 10 183
#> 20.90 16.47 16.67 23.41 15.55 10.55 19.34 21.19 20.90 23.23 19.34 10.53 9.24
#> 154 179 167.1 85 93.1 51 24 66 123 164 76 16 157
#> 12.63 18.63 15.55 16.44 10.33 18.23 23.89 22.13 13.00 23.60 19.22 8.71 15.10
#> 181 164.1 168 171 134 56 170 129.1 179.1 13 181.1 145.1 77
#> 16.46 23.60 23.72 16.57 17.81 12.21 19.54 23.41 18.63 14.34 16.46 10.07 7.27
#> 167.2 10.1 183.1 93.2 106.1 158 25.2 10.2 30 164.2 29 36 14
#> 15.55 10.53 9.24 10.33 16.67 20.14 6.32 10.53 17.43 23.60 15.45 21.19 12.89
#> 68 127 56.1 13.1 24.1 16.1 36.1 134.1 180 197 194 5 113
#> 20.62 3.53 12.21 14.34 23.89 8.71 21.19 17.81 14.82 21.60 22.40 16.43 22.86
#> 150 14.1 171.1 25.3 139 14.2 92.1 153 194.1 154.1 128.1 117 23
#> 20.33 12.89 16.57 6.32 21.49 12.89 22.92 21.33 22.40 12.63 20.35 17.46 16.92
#> 66.1 5.1 159.1 39 8.1 169.1 105 133 190 52 70 108 39.1
#> 22.13 16.43 10.55 15.59 18.43 22.41 19.75 14.65 20.81 10.42 7.38 18.29 15.59
#> 34 82 119 7 11 109 3 132 9 28 103 53 119.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 84 31 1 1.1 185 138 38 103.1 33 162 22 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 94 12 160 141 146 144 47 135 11.1 35 17 80.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 103.2 182 98 64 34.1 121 148 146.1 2 122 35.1 135.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 80.2 47.1 176 163 74 54 185.1 65 200 83 95 84.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182.1 12.1 31.1 126 109.1 174 160.1 11.2 162.1 48 138.1 94.1 82.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 172 34.2 11.3 48.1 74.1 64.1 33.1 35.2 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[30]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004758418 0.254106758 0.217381318
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.256820207 -0.006563578 0.016304434
#> grade_iii, Cure model
#> 0.653511015
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 192 16.44 1 31 1 0
#> 187 9.92 1 39 1 0
#> 153 21.33 1 55 1 0
#> 39 15.59 1 37 0 1
#> 92 22.92 1 47 0 1
#> 63 22.77 1 31 1 0
#> 18 15.21 1 49 1 0
#> 29 15.45 1 68 1 0
#> 90 20.94 1 50 0 1
#> 23 16.92 1 61 0 0
#> 63.1 22.77 1 31 1 0
#> 139 21.49 1 63 1 0
#> 79 16.23 1 54 1 0
#> 128 20.35 1 35 0 1
#> 45 17.42 1 54 0 1
#> 85 16.44 1 36 0 0
#> 139.1 21.49 1 63 1 0
#> 10 10.53 1 34 0 0
#> 14 12.89 1 21 0 0
#> 39.1 15.59 1 37 0 1
#> 168 23.72 1 70 0 0
#> 66 22.13 1 53 0 0
#> 124 9.73 1 NA 1 0
#> 92.1 22.92 1 47 0 1
#> 51 18.23 1 83 0 1
#> 183 9.24 1 67 1 0
#> 13 14.34 1 54 0 1
#> 68 20.62 1 44 0 0
#> 23.1 16.92 1 61 0 0
#> 184 17.77 1 38 0 0
#> 133 14.65 1 57 0 0
#> 68.1 20.62 1 44 0 0
#> 5 16.43 1 51 0 1
#> 111 17.45 1 47 0 1
#> 124.1 9.73 1 NA 1 0
#> 159 10.55 1 50 0 1
#> 15 22.68 1 48 0 0
#> 10.1 10.53 1 34 0 0
#> 124.2 9.73 1 NA 1 0
#> 111.1 17.45 1 47 0 1
#> 167 15.55 1 56 1 0
#> 199 19.81 1 NA 0 1
#> 155 13.08 1 26 0 0
#> 45.1 17.42 1 54 0 1
#> 68.2 20.62 1 44 0 0
#> 136 21.83 1 43 0 1
#> 93 10.33 1 52 0 1
#> 61 10.12 1 36 0 1
#> 136.1 21.83 1 43 0 1
#> 49 12.19 1 48 1 0
#> 36 21.19 1 48 0 1
#> 170 19.54 1 43 0 1
#> 159.1 10.55 1 50 0 1
#> 106 16.67 1 49 1 0
#> 4 17.64 1 NA 0 1
#> 181 16.46 1 45 0 1
#> 63.2 22.77 1 31 1 0
#> 155.1 13.08 1 26 0 0
#> 101 9.97 1 10 0 1
#> 18.1 15.21 1 49 1 0
#> 51.1 18.23 1 83 0 1
#> 8 18.43 1 32 0 0
#> 106.1 16.67 1 49 1 0
#> 136.2 21.83 1 43 0 1
#> 154 12.63 1 20 1 0
#> 4.1 17.64 1 NA 0 1
#> 88 18.37 1 47 0 0
#> 129 23.41 1 53 1 0
#> 90.1 20.94 1 50 0 1
#> 76 19.22 1 54 0 1
#> 190 20.81 1 42 1 0
#> 155.2 13.08 1 26 0 0
#> 26 15.77 1 49 0 1
#> 181.1 16.46 1 45 0 1
#> 51.2 18.23 1 83 0 1
#> 96 14.54 1 33 0 1
#> 24 23.89 1 38 0 0
#> 10.2 10.53 1 34 0 0
#> 15.1 22.68 1 48 0 0
#> 6 15.64 1 39 0 0
#> 60 13.15 1 38 1 0
#> 130 16.47 1 53 0 1
#> 32 20.90 1 37 1 0
#> 25 6.32 1 34 1 0
#> 13.1 14.34 1 54 0 1
#> 18.2 15.21 1 49 1 0
#> 56 12.21 1 60 0 0
#> 14.1 12.89 1 21 0 0
#> 32.1 20.90 1 37 1 0
#> 77 7.27 1 67 0 1
#> 113 22.86 1 34 0 0
#> 170.1 19.54 1 43 0 1
#> 18.3 15.21 1 49 1 0
#> 108 18.29 1 39 0 1
#> 194 22.40 1 38 0 1
#> 5.1 16.43 1 51 0 1
#> 39.2 15.59 1 37 0 1
#> 93.1 10.33 1 52 0 1
#> 39.3 15.59 1 37 0 1
#> 93.2 10.33 1 52 0 1
#> 158 20.14 1 74 1 0
#> 24.1 23.89 1 38 0 0
#> 8.1 18.43 1 32 0 0
#> 68.3 20.62 1 44 0 0
#> 150 20.33 1 48 0 0
#> 43 12.10 1 61 0 1
#> 92.2 22.92 1 47 0 1
#> 93.3 10.33 1 52 0 1
#> 86 23.81 1 58 0 1
#> 36.1 21.19 1 48 0 1
#> 92.3 22.92 1 47 0 1
#> 194.1 22.40 1 38 0 1
#> 115 24.00 0 NA 1 0
#> 17 24.00 0 38 0 1
#> 142 24.00 0 53 0 0
#> 75 24.00 0 21 1 0
#> 64 24.00 0 43 0 0
#> 193 24.00 0 45 0 1
#> 31 24.00 0 36 0 1
#> 109 24.00 0 48 0 0
#> 28 24.00 0 67 1 0
#> 135 24.00 0 58 1 0
#> 103 24.00 0 56 1 0
#> 46 24.00 0 71 0 0
#> 174 24.00 0 49 1 0
#> 144 24.00 0 28 0 1
#> 82 24.00 0 34 0 0
#> 185 24.00 0 44 1 0
#> 142.1 24.00 0 53 0 0
#> 119 24.00 0 17 0 0
#> 33 24.00 0 53 0 0
#> 148 24.00 0 61 1 0
#> 162 24.00 0 51 0 0
#> 74 24.00 0 43 0 1
#> 131 24.00 0 66 0 0
#> 12 24.00 0 63 0 0
#> 141 24.00 0 44 1 0
#> 121 24.00 0 57 1 0
#> 119.1 24.00 0 17 0 0
#> 162.1 24.00 0 51 0 0
#> 103.1 24.00 0 56 1 0
#> 172 24.00 0 41 0 0
#> 98 24.00 0 34 1 0
#> 31.1 24.00 0 36 0 1
#> 102 24.00 0 49 0 0
#> 193.1 24.00 0 45 0 1
#> 20 24.00 0 46 1 0
#> 94 24.00 0 51 0 1
#> 17.1 24.00 0 38 0 1
#> 73 24.00 0 NA 0 1
#> 126 24.00 0 48 0 0
#> 7 24.00 0 37 1 0
#> 191 24.00 0 60 0 1
#> 120 24.00 0 68 0 1
#> 1 24.00 0 23 1 0
#> 19 24.00 0 57 0 1
#> 148.1 24.00 0 61 1 0
#> 137 24.00 0 45 1 0
#> 102.1 24.00 0 49 0 0
#> 47 24.00 0 38 0 1
#> 9 24.00 0 31 1 0
#> 33.1 24.00 0 53 0 0
#> 17.2 24.00 0 38 0 1
#> 7.1 24.00 0 37 1 0
#> 165 24.00 0 47 0 0
#> 119.2 24.00 0 17 0 0
#> 147 24.00 0 76 1 0
#> 103.2 24.00 0 56 1 0
#> 131.1 24.00 0 66 0 0
#> 82.1 24.00 0 34 0 0
#> 38 24.00 0 31 1 0
#> 126.1 24.00 0 48 0 0
#> 102.2 24.00 0 49 0 0
#> 53 24.00 0 32 0 1
#> 22 24.00 0 52 1 0
#> 98.1 24.00 0 34 1 0
#> 109.1 24.00 0 48 0 0
#> 193.2 24.00 0 45 0 1
#> 112 24.00 0 61 0 0
#> 102.3 24.00 0 49 0 0
#> 198 24.00 0 66 0 1
#> 173 24.00 0 19 0 1
#> 118 24.00 0 44 1 0
#> 54 24.00 0 53 1 0
#> 152 24.00 0 36 0 1
#> 95 24.00 0 68 0 1
#> 62 24.00 0 71 0 0
#> 35 24.00 0 51 0 0
#> 95.1 24.00 0 68 0 1
#> 176 24.00 0 43 0 1
#> 120.1 24.00 0 68 0 1
#> 146 24.00 0 63 1 0
#> 31.2 24.00 0 36 0 1
#> 148.2 24.00 0 61 1 0
#> 95.2 24.00 0 68 0 1
#> 83 24.00 0 6 0 0
#> 17.3 24.00 0 38 0 1
#> 176.1 24.00 0 43 0 1
#> 38.1 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.257 NA NA NA
#> 2 age, Cure model -0.00656 NA NA NA
#> 3 grade_ii, Cure model 0.0163 NA NA NA
#> 4 grade_iii, Cure model 0.654 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00476 NA NA NA
#> 2 grade_ii, Survival model 0.254 NA NA NA
#> 3 grade_iii, Survival model 0.217 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.256820 -0.006564 0.016304 0.653511
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.1
#> Residual Deviance: 259.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.256820207 -0.006563578 0.016304434 0.653511015
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004758418 0.254106758 0.217381318
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.553264810 0.960598066 0.207228312 0.621170962 0.051241546 0.092512946
#> [7] 0.678736660 0.668990937 0.234625410 0.485647195 0.092512946 0.189131056
#> [13] 0.591905119 0.315790998 0.466539537 0.553264810 0.189131056 0.872715921
#> [19] 0.794461643 0.621170962 0.030121990 0.153425609 0.051241546 0.409635347
#> [25] 0.970441447 0.736343226 0.280026332 0.485647195 0.437822443 0.716843193
#> [31] 0.280026332 0.572576792 0.447462299 0.853182147 0.117620638 0.872715921
#> [37] 0.447462299 0.659254734 0.765470674 0.466539537 0.280026332 0.162756898
#> [43] 0.901998117 0.940878064 0.162756898 0.833552510 0.216486823 0.343926996
#> [49] 0.853182147 0.504946224 0.533968033 0.092512946 0.765470674 0.950747526
#> [55] 0.678736660 0.409635347 0.371893360 0.504946224 0.162756898 0.813953845
#> [61] 0.390606907 0.040676479 0.234625410 0.362483660 0.270856297 0.765470674
#> [67] 0.601649951 0.533968033 0.409635347 0.726597278 0.006198109 0.872715921
#> [73] 0.117620638 0.611397259 0.755725932 0.524229746 0.252793240 0.990150287
#> [79] 0.736343226 0.678736660 0.823738700 0.794461643 0.252793240 0.980291089
#> [85] 0.082941596 0.343926996 0.678736660 0.400124777 0.135565348 0.572576792
#> [91] 0.621170962 0.901998117 0.621170962 0.901998117 0.334513523 0.006198109
#> [97] 0.371893360 0.280026332 0.325124734 0.843363314 0.051241546 0.901998117
#> [103] 0.020541424 0.216486823 0.051241546 0.135565348 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 192 187 153 39 92 63 18 29 90 23 63.1 139 79
#> 16.44 9.92 21.33 15.59 22.92 22.77 15.21 15.45 20.94 16.92 22.77 21.49 16.23
#> 128 45 85 139.1 10 14 39.1 168 66 92.1 51 183 13
#> 20.35 17.42 16.44 21.49 10.53 12.89 15.59 23.72 22.13 22.92 18.23 9.24 14.34
#> 68 23.1 184 133 68.1 5 111 159 15 10.1 111.1 167 155
#> 20.62 16.92 17.77 14.65 20.62 16.43 17.45 10.55 22.68 10.53 17.45 15.55 13.08
#> 45.1 68.2 136 93 61 136.1 49 36 170 159.1 106 181 63.2
#> 17.42 20.62 21.83 10.33 10.12 21.83 12.19 21.19 19.54 10.55 16.67 16.46 22.77
#> 155.1 101 18.1 51.1 8 106.1 136.2 154 88 129 90.1 76 190
#> 13.08 9.97 15.21 18.23 18.43 16.67 21.83 12.63 18.37 23.41 20.94 19.22 20.81
#> 155.2 26 181.1 51.2 96 24 10.2 15.1 6 60 130 32 25
#> 13.08 15.77 16.46 18.23 14.54 23.89 10.53 22.68 15.64 13.15 16.47 20.90 6.32
#> 13.1 18.2 56 14.1 32.1 77 113 170.1 18.3 108 194 5.1 39.2
#> 14.34 15.21 12.21 12.89 20.90 7.27 22.86 19.54 15.21 18.29 22.40 16.43 15.59
#> 93.1 39.3 93.2 158 24.1 8.1 68.3 150 43 92.2 93.3 86 36.1
#> 10.33 15.59 10.33 20.14 23.89 18.43 20.62 20.33 12.10 22.92 10.33 23.81 21.19
#> 92.3 194.1 17 142 75 64 193 31 109 28 135 103 46
#> 22.92 22.40 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 144 82 185 142.1 119 33 148 162 74 131 12 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 119.1 162.1 103.1 172 98 31.1 102 193.1 20 94 17.1 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 191 120 1 19 148.1 137 102.1 47 9 33.1 17.2 7.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 119.2 147 103.2 131.1 82.1 38 126.1 102.2 53 22 98.1 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193.2 112 102.3 198 173 118 54 152 95 62 35 95.1 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120.1 146 31.2 148.2 95.2 83 17.3 176.1 38.1 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[31]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003155754 0.439576084 0.309005802
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.18393485 0.02065103 0.42914565
#> grade_iii, Cure model
#> 0.89804467
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 96 14.54 1 33 0 1
#> 97 19.14 1 65 0 1
#> 18 15.21 1 49 1 0
#> 139 21.49 1 63 1 0
#> 123 13.00 1 44 1 0
#> 169 22.41 1 46 0 0
#> 25 6.32 1 34 1 0
#> 195 11.76 1 NA 1 0
#> 55 19.34 1 69 0 1
#> 150 20.33 1 48 0 0
#> 134 17.81 1 47 1 0
#> 37 12.52 1 57 1 0
#> 107 11.18 1 54 1 0
#> 4 17.64 1 NA 0 1
#> 189 10.51 1 NA 1 0
#> 170 19.54 1 43 0 1
#> 117 17.46 1 26 0 1
#> 69 23.23 1 25 0 1
#> 69.1 23.23 1 25 0 1
#> 130 16.47 1 53 0 1
#> 49 12.19 1 48 1 0
#> 197 21.60 1 69 1 0
#> 188 16.16 1 46 0 1
#> 25.1 6.32 1 34 1 0
#> 127 3.53 1 62 0 1
#> 157 15.10 1 47 0 0
#> 153 21.33 1 55 1 0
#> 197.1 21.60 1 69 1 0
#> 68 20.62 1 44 0 0
#> 13 14.34 1 54 0 1
#> 180 14.82 1 37 0 0
#> 183 9.24 1 67 1 0
#> 129 23.41 1 53 1 0
#> 63 22.77 1 31 1 0
#> 187 9.92 1 39 1 0
#> 180.1 14.82 1 37 0 0
#> 5 16.43 1 51 0 1
#> 130.1 16.47 1 53 0 1
#> 42 12.43 1 49 0 1
#> 37.1 12.52 1 57 1 0
#> 52 10.42 1 52 0 1
#> 5.1 16.43 1 51 0 1
#> 52.1 10.42 1 52 0 1
#> 88 18.37 1 47 0 0
#> 124 9.73 1 NA 1 0
#> 181 16.46 1 45 0 1
#> 189.1 10.51 1 NA 1 0
#> 61 10.12 1 36 0 1
#> 183.1 9.24 1 67 1 0
#> 183.2 9.24 1 67 1 0
#> 140 12.68 1 59 1 0
#> 36 21.19 1 48 0 1
#> 14 12.89 1 21 0 0
#> 66 22.13 1 53 0 0
#> 76 19.22 1 54 0 1
#> 51 18.23 1 83 0 1
#> 114 13.68 1 NA 0 0
#> 117.1 17.46 1 26 0 1
#> 24 23.89 1 38 0 0
#> 55.1 19.34 1 69 0 1
#> 50 10.02 1 NA 1 0
#> 13.1 14.34 1 54 0 1
#> 8 18.43 1 32 0 0
#> 13.2 14.34 1 54 0 1
#> 13.3 14.34 1 54 0 1
#> 197.2 21.60 1 69 1 0
#> 184 17.77 1 38 0 0
#> 66.1 22.13 1 53 0 0
#> 14.1 12.89 1 21 0 0
#> 187.1 9.92 1 39 1 0
#> 68.1 20.62 1 44 0 0
#> 16 8.71 1 71 0 1
#> 134.1 17.81 1 47 1 0
#> 24.1 23.89 1 38 0 0
#> 158 20.14 1 74 1 0
#> 14.2 12.89 1 21 0 0
#> 18.1 15.21 1 49 1 0
#> 36.1 21.19 1 48 0 1
#> 123.1 13.00 1 44 1 0
#> 171 16.57 1 41 0 1
#> 63.1 22.77 1 31 1 0
#> 150.1 20.33 1 48 0 0
#> 85 16.44 1 36 0 0
#> 117.2 17.46 1 26 0 1
#> 36.2 21.19 1 48 0 1
#> 49.1 12.19 1 48 1 0
#> 97.1 19.14 1 65 0 1
#> 25.2 6.32 1 34 1 0
#> 155 13.08 1 26 0 0
#> 69.2 23.23 1 25 0 1
#> 108 18.29 1 39 0 1
#> 107.1 11.18 1 54 1 0
#> 167 15.55 1 56 1 0
#> 92 22.92 1 47 0 1
#> 106 16.67 1 49 1 0
#> 58 19.34 1 39 0 0
#> 99 21.19 1 38 0 1
#> 107.2 11.18 1 54 1 0
#> 85.1 16.44 1 36 0 0
#> 32 20.90 1 37 1 0
#> 111 17.45 1 47 0 1
#> 37.2 12.52 1 57 1 0
#> 105 19.75 1 60 0 0
#> 197.3 21.60 1 69 1 0
#> 134.2 17.81 1 47 1 0
#> 134.3 17.81 1 47 1 0
#> 45 17.42 1 54 0 1
#> 50.1 10.02 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 49.2 12.19 1 48 1 0
#> 61.1 10.12 1 36 0 1
#> 170.1 19.54 1 43 0 1
#> 172 24.00 0 41 0 0
#> 47 24.00 0 38 0 1
#> 67 24.00 0 25 0 0
#> 53 24.00 0 32 0 1
#> 2 24.00 0 9 0 0
#> 126 24.00 0 48 0 0
#> 21 24.00 0 47 0 0
#> 143 24.00 0 51 0 0
#> 11 24.00 0 42 0 1
#> 196 24.00 0 19 0 0
#> 162 24.00 0 51 0 0
#> 162.1 24.00 0 51 0 0
#> 160 24.00 0 31 1 0
#> 135 24.00 0 58 1 0
#> 119 24.00 0 17 0 0
#> 64 24.00 0 43 0 0
#> 143.1 24.00 0 51 0 0
#> 174 24.00 0 49 1 0
#> 48 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 141 24.00 0 44 1 0
#> 72 24.00 0 40 0 1
#> 144 24.00 0 28 0 1
#> 115 24.00 0 NA 1 0
#> 19 24.00 0 57 0 1
#> 34 24.00 0 36 0 0
#> 122 24.00 0 66 0 0
#> 74 24.00 0 43 0 1
#> 115.1 24.00 0 NA 1 0
#> 172.1 24.00 0 41 0 0
#> 102 24.00 0 49 0 0
#> 120.1 24.00 0 68 0 1
#> 116 24.00 0 58 0 1
#> 27 24.00 0 63 1 0
#> 87 24.00 0 27 0 0
#> 119.1 24.00 0 17 0 0
#> 178 24.00 0 52 1 0
#> 146 24.00 0 63 1 0
#> 3 24.00 0 31 1 0
#> 3.1 24.00 0 31 1 0
#> 54 24.00 0 53 1 0
#> 27.1 24.00 0 63 1 0
#> 135.1 24.00 0 58 1 0
#> 120.2 24.00 0 68 0 1
#> 141.1 24.00 0 44 1 0
#> 131 24.00 0 66 0 0
#> 104 24.00 0 50 1 0
#> 200 24.00 0 64 0 0
#> 38 24.00 0 31 1 0
#> 160.1 24.00 0 31 1 0
#> 160.2 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 1 24.00 0 23 1 0
#> 193 24.00 0 45 0 1
#> 165 24.00 0 47 0 0
#> 143.2 24.00 0 51 0 0
#> 7 24.00 0 37 1 0
#> 22 24.00 0 52 1 0
#> 83 24.00 0 6 0 0
#> 176 24.00 0 43 0 1
#> 160.3 24.00 0 31 1 0
#> 1.1 24.00 0 23 1 0
#> 11.1 24.00 0 42 0 1
#> 34.1 24.00 0 36 0 0
#> 9 24.00 0 31 1 0
#> 102.1 24.00 0 49 0 0
#> 82 24.00 0 34 0 0
#> 73 24.00 0 NA 0 1
#> 186 24.00 0 45 1 0
#> 193.1 24.00 0 45 0 1
#> 104.1 24.00 0 50 1 0
#> 17 24.00 0 38 0 1
#> 146.1 24.00 0 63 1 0
#> 200.1 24.00 0 64 0 0
#> 74.1 24.00 0 43 0 1
#> 176.1 24.00 0 43 0 1
#> 143.3 24.00 0 51 0 0
#> 20 24.00 0 46 1 0
#> 143.4 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 119.2 24.00 0 17 0 0
#> 160.4 24.00 0 31 1 0
#> 144.1 24.00 0 28 0 1
#> 118.1 24.00 0 44 1 0
#> 152 24.00 0 36 0 1
#> 47.1 24.00 0 38 0 1
#> 12 24.00 0 63 0 0
#> 33 24.00 0 53 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.18 NA NA NA
#> 2 age, Cure model 0.0207 NA NA NA
#> 3 grade_ii, Cure model 0.429 NA NA NA
#> 4 grade_iii, Cure model 0.898 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00316 NA NA NA
#> 2 grade_ii, Survival model 0.440 NA NA NA
#> 3 grade_iii, Survival model 0.309 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.18393 0.02065 0.42915 0.89804
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.1
#> Residual Deviance: 249.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.18393485 0.02065103 0.42914565 0.89804467
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003155754 0.439576084 0.309005802
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.76223094 0.49906654 0.72572438 0.30898805 0.80467318 0.21835675
#> [7] 0.97566100 0.46235602 0.40335570 0.55251325 0.84637304 0.89314774
#> [13] 0.44326923 0.59347187 0.11988756 0.11988756 0.64955966 0.87337295
#> [19] 0.26288194 0.70317112 0.97566100 0.99390552 0.74034009 0.32080431
#> [25] 0.26288194 0.38310355 0.76950940 0.74767274 0.95087752 0.09388032
#> [31] 0.18831871 0.93822346 0.74767274 0.68805716 0.64955966 0.86660657
#> [37] 0.84637304 0.91256134 0.68805716 0.91256134 0.52590040 0.66501816
#> [43] 0.92543918 0.95087752 0.95087752 0.83943054 0.33226348 0.81862640
#> [49] 0.23376009 0.48983743 0.54374263 0.59347187 0.03866861 0.46235602
#> [55] 0.76950940 0.51691460 0.76950940 0.76950940 0.26288194 0.58515107
#> [61] 0.23376009 0.81862640 0.93822346 0.38310355 0.96945620 0.55251325
#> [67] 0.03866861 0.42344313 0.81862640 0.72572438 0.33226348 0.80467318
#> [73] 0.64166862 0.18831871 0.40335570 0.67274140 0.59347187 0.33226348
#> [79] 0.87337295 0.49906654 0.97566100 0.79756916 0.11988756 0.53486172
#> [85] 0.89314774 0.71825669 0.17055140 0.63372384 0.46235602 0.33226348
#> [91] 0.89314774 0.67274140 0.37275756 0.61760709 0.84637304 0.43337981
#> [97] 0.26288194 0.55251325 0.55251325 0.62569738 0.71072225 0.87337295
#> [103] 0.92543918 0.44326923 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 96 97 18 139 123 169 25 55 150 134 37 107 170
#> 14.54 19.14 15.21 21.49 13.00 22.41 6.32 19.34 20.33 17.81 12.52 11.18 19.54
#> 117 69 69.1 130 49 197 188 25.1 127 157 153 197.1 68
#> 17.46 23.23 23.23 16.47 12.19 21.60 16.16 6.32 3.53 15.10 21.33 21.60 20.62
#> 13 180 183 129 63 187 180.1 5 130.1 42 37.1 52 5.1
#> 14.34 14.82 9.24 23.41 22.77 9.92 14.82 16.43 16.47 12.43 12.52 10.42 16.43
#> 52.1 88 181 61 183.1 183.2 140 36 14 66 76 51 117.1
#> 10.42 18.37 16.46 10.12 9.24 9.24 12.68 21.19 12.89 22.13 19.22 18.23 17.46
#> 24 55.1 13.1 8 13.2 13.3 197.2 184 66.1 14.1 187.1 68.1 16
#> 23.89 19.34 14.34 18.43 14.34 14.34 21.60 17.77 22.13 12.89 9.92 20.62 8.71
#> 134.1 24.1 158 14.2 18.1 36.1 123.1 171 63.1 150.1 85 117.2 36.2
#> 17.81 23.89 20.14 12.89 15.21 21.19 13.00 16.57 22.77 20.33 16.44 17.46 21.19
#> 49.1 97.1 25.2 155 69.2 108 107.1 167 92 106 58 99 107.2
#> 12.19 19.14 6.32 13.08 23.23 18.29 11.18 15.55 22.92 16.67 19.34 21.19 11.18
#> 85.1 32 111 37.2 105 197.3 134.2 134.3 45 100 49.2 61.1 170.1
#> 16.44 20.90 17.45 12.52 19.75 21.60 17.81 17.81 17.42 16.07 12.19 10.12 19.54
#> 172 47 67 53 2 126 21 143 11 196 162 162.1 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 119 64 143.1 174 48 120 141 72 144 19 34 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74 172.1 102 120.1 116 27 87 119.1 178 146 3 3.1 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27.1 135.1 120.2 141.1 131 104 200 38 160.1 160.2 118 1 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 143.2 7 22 83 176 160.3 1.1 11.1 34.1 9 102.1 82
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 193.1 104.1 17 146.1 200.1 74.1 176.1 143.3 20 143.4 44 119.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160.4 144.1 118.1 152 47.1 12 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[32]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01576332 0.56700078 0.14529805
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.0423282921 -0.0009973394 -0.2634291135
#> grade_iii, Cure model
#> 0.8832327815
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 134 17.81 1 47 1 0
#> 8 18.43 1 32 0 0
#> 8.1 18.43 1 32 0 0
#> 86 23.81 1 58 0 1
#> 125 15.65 1 67 1 0
#> 97 19.14 1 65 0 1
#> 181 16.46 1 45 0 1
#> 39 15.59 1 37 0 1
#> 127 3.53 1 62 0 1
#> 91 5.33 1 61 0 1
#> 117 17.46 1 26 0 1
#> 92 22.92 1 47 0 1
#> 171 16.57 1 41 0 1
#> 15 22.68 1 48 0 0
#> 40 18.00 1 28 1 0
#> 88 18.37 1 47 0 0
#> 29 15.45 1 68 1 0
#> 90 20.94 1 50 0 1
#> 76 19.22 1 54 0 1
#> 58 19.34 1 39 0 0
#> 57 14.46 1 45 0 1
#> 113 22.86 1 34 0 0
#> 188 16.16 1 46 0 1
#> 14 12.89 1 21 0 0
#> 97.1 19.14 1 65 0 1
#> 26 15.77 1 49 0 1
#> 66 22.13 1 53 0 0
#> 68 20.62 1 44 0 0
#> 187 9.92 1 39 1 0
#> 100 16.07 1 60 0 0
#> 99 21.19 1 38 0 1
#> 43 12.10 1 61 0 1
#> 108 18.29 1 39 0 1
#> 106 16.67 1 49 1 0
#> 51 18.23 1 83 0 1
#> 96 14.54 1 33 0 1
#> 194 22.40 1 38 0 1
#> 150 20.33 1 48 0 0
#> 105 19.75 1 60 0 0
#> 110 17.56 1 65 0 1
#> 124 9.73 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 36 21.19 1 48 0 1
#> 184 17.77 1 38 0 0
#> 40.1 18.00 1 28 1 0
#> 106.1 16.67 1 49 1 0
#> 164 23.60 1 76 0 1
#> 16 8.71 1 71 0 1
#> 57.1 14.46 1 45 0 1
#> 197 21.60 1 69 1 0
#> 117.1 17.46 1 26 0 1
#> 169 22.41 1 46 0 0
#> 111 17.45 1 47 0 1
#> 113.1 22.86 1 34 0 0
#> 134.1 17.81 1 47 1 0
#> 58.1 19.34 1 39 0 0
#> 154 12.63 1 20 1 0
#> 59 10.16 1 NA 1 0
#> 40.2 18.00 1 28 1 0
#> 157 15.10 1 47 0 0
#> 194.1 22.40 1 38 0 1
#> 184.1 17.77 1 38 0 0
#> 85 16.44 1 36 0 0
#> 150.1 20.33 1 48 0 0
#> 14.1 12.89 1 21 0 0
#> 86.1 23.81 1 58 0 1
#> 187.1 9.92 1 39 1 0
#> 99.1 21.19 1 38 0 1
#> 150.2 20.33 1 48 0 0
#> 60 13.15 1 38 1 0
#> 6 15.64 1 39 0 0
#> 4 17.64 1 NA 0 1
#> 15.1 22.68 1 48 0 0
#> 158 20.14 1 74 1 0
#> 51.1 18.23 1 83 0 1
#> 101 9.97 1 10 0 1
#> 57.2 14.46 1 45 0 1
#> 4.1 17.64 1 NA 0 1
#> 32 20.90 1 37 1 0
#> 199 19.81 1 NA 0 1
#> 130 16.47 1 53 0 1
#> 68.1 20.62 1 44 0 0
#> 140 12.68 1 59 1 0
#> 157.1 15.10 1 47 0 0
#> 32.1 20.90 1 37 1 0
#> 164.1 23.60 1 76 0 1
#> 86.2 23.81 1 58 0 1
#> 128 20.35 1 35 0 1
#> 180 14.82 1 37 0 0
#> 188.1 16.16 1 46 0 1
#> 14.2 12.89 1 21 0 0
#> 133 14.65 1 57 0 0
#> 78 23.88 1 43 0 0
#> 70 7.38 1 30 1 0
#> 101.1 9.97 1 10 0 1
#> 124.1 9.73 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 177 12.53 1 75 0 0
#> 63 22.77 1 31 1 0
#> 187.2 9.92 1 39 1 0
#> 111.1 17.45 1 47 0 1
#> 52 10.42 1 52 0 1
#> 91.1 5.33 1 61 0 1
#> 124.2 9.73 1 NA 1 0
#> 90.1 20.94 1 50 0 1
#> 127.1 3.53 1 62 0 1
#> 157.2 15.10 1 47 0 0
#> 51.2 18.23 1 83 0 1
#> 154.1 12.63 1 20 1 0
#> 155 13.08 1 26 0 0
#> 149 8.37 1 33 1 0
#> 86.3 23.81 1 58 0 1
#> 73 24.00 0 NA 0 1
#> 72 24.00 0 40 0 1
#> 87 24.00 0 27 0 0
#> 156 24.00 0 50 1 0
#> 9 24.00 0 31 1 0
#> 84 24.00 0 39 0 1
#> 95 24.00 0 68 0 1
#> 2 24.00 0 9 0 0
#> 178 24.00 0 52 1 0
#> 112 24.00 0 61 0 0
#> 200 24.00 0 64 0 0
#> 53 24.00 0 32 0 1
#> 46 24.00 0 71 0 0
#> 87.1 24.00 0 27 0 0
#> 7 24.00 0 37 1 0
#> 1 24.00 0 23 1 0
#> 34 24.00 0 36 0 0
#> 163 24.00 0 66 0 0
#> 115 24.00 0 NA 1 0
#> 2.1 24.00 0 9 0 0
#> 163.1 24.00 0 66 0 0
#> 121 24.00 0 57 1 0
#> 94 24.00 0 51 0 1
#> 116 24.00 0 58 0 1
#> 120 24.00 0 68 0 1
#> 67 24.00 0 25 0 0
#> 9.1 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 193 24.00 0 45 0 1
#> 143 24.00 0 51 0 0
#> 27 24.00 0 63 1 0
#> 84.1 24.00 0 39 0 1
#> 191 24.00 0 60 0 1
#> 156.1 24.00 0 50 1 0
#> 115.1 24.00 0 NA 1 0
#> 27.1 24.00 0 63 1 0
#> 144 24.00 0 28 0 1
#> 75 24.00 0 21 1 0
#> 103 24.00 0 56 1 0
#> 17 24.00 0 38 0 1
#> 185 24.00 0 44 1 0
#> 103.1 24.00 0 56 1 0
#> 120.1 24.00 0 68 0 1
#> 67.1 24.00 0 25 0 0
#> 120.2 24.00 0 68 0 1
#> 83 24.00 0 6 0 0
#> 7.1 24.00 0 37 1 0
#> 182 24.00 0 35 0 0
#> 7.2 24.00 0 37 1 0
#> 151 24.00 0 42 0 0
#> 9.2 24.00 0 31 1 0
#> 196 24.00 0 19 0 0
#> 67.2 24.00 0 25 0 0
#> 193.1 24.00 0 45 0 1
#> 38 24.00 0 31 1 0
#> 64 24.00 0 43 0 0
#> 28 24.00 0 67 1 0
#> 73.1 24.00 0 NA 0 1
#> 46.1 24.00 0 71 0 0
#> 185.1 24.00 0 44 1 0
#> 103.2 24.00 0 56 1 0
#> 74 24.00 0 43 0 1
#> 120.3 24.00 0 68 0 1
#> 71 24.00 0 51 0 0
#> 146 24.00 0 63 1 0
#> 21.1 24.00 0 47 0 0
#> 122 24.00 0 66 0 0
#> 53.1 24.00 0 32 0 1
#> 75.1 24.00 0 21 1 0
#> 28.1 24.00 0 67 1 0
#> 12 24.00 0 63 0 0
#> 17.1 24.00 0 38 0 1
#> 19 24.00 0 57 0 1
#> 132 24.00 0 55 0 0
#> 196.1 24.00 0 19 0 0
#> 109 24.00 0 48 0 0
#> 121.1 24.00 0 57 1 0
#> 87.2 24.00 0 27 0 0
#> 20 24.00 0 46 1 0
#> 35 24.00 0 51 0 0
#> 172 24.00 0 41 0 0
#> 146.1 24.00 0 63 1 0
#> 38.1 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 65 24.00 0 57 1 0
#> 54 24.00 0 53 1 0
#> 34.1 24.00 0 36 0 0
#> 102 24.00 0 49 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.0423 NA NA NA
#> 2 age, Cure model -0.000997 NA NA NA
#> 3 grade_ii, Cure model -0.263 NA NA NA
#> 4 grade_iii, Cure model 0.883 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0158 NA NA NA
#> 2 grade_ii, Survival model 0.567 NA NA NA
#> 3 grade_iii, Survival model 0.145 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.0423283 -0.0009973 -0.2634291 0.8832328
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 259.7
#> Residual Deviance: 249.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.0423282921 -0.0009973394 -0.2634291135 0.8832327815
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01576332 0.56700078 0.14529805
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 2.879913e-01 1.936293e-01 1.936293e-01 7.081412e-04 4.968442e-01
#> [6] 1.766192e-01 4.259194e-01 5.216638e-01 9.695916e-01 9.397125e-01
#> [11] 3.387334e-01 1.007050e-02 4.033391e-01 2.255276e-02 2.591214e-01
#> [16] 2.112533e-01 5.342498e-01 7.366879e-02 1.683756e-01 1.526716e-01
#> [21] 6.259032e-01 1.297790e-02 4.490500e-01 6.948455e-01 1.766192e-01
#> [26] 4.846213e-01 4.263039e-02 9.747722e-02 8.519479e-01 4.725404e-01
#> [31] 5.774217e-02 7.937082e-01 2.204626e-01 3.814602e-01 2.298184e-01
#> [36] 6.123362e-01 3.403997e-02 1.168486e-01 1.449804e-01 3.281800e-01
#> [41] 3.852039e-03 5.774217e-02 3.077900e-01 2.591214e-01 3.814602e-01
#> [46] 5.583859e-03 8.952674e-01 6.259032e-01 5.249788e-02 3.387334e-01
#> [51] 2.985199e-02 3.598121e-01 1.297790e-02 2.879913e-01 1.526716e-01
#> [56] 7.511952e-01 2.591214e-01 5.469545e-01 3.403997e-02 3.077900e-01
#> [61] 4.374185e-01 1.168486e-01 6.948455e-01 7.081412e-04 8.519479e-01
#> [66] 5.774217e-02 1.168486e-01 6.668523e-01 5.091845e-01 2.255276e-02
#> [71] 1.375309e-01 2.298184e-01 8.228876e-01 6.259032e-01 8.555834e-02
#> [76] 4.145526e-01 9.747722e-02 7.368383e-01 5.469545e-01 8.555834e-02
#> [81] 5.583859e-03 7.081412e-04 1.101737e-01 5.855661e-01 4.490500e-01
#> [86] 6.948455e-01 5.988624e-01 9.879613e-05 9.249169e-01 8.228876e-01
#> [91] 4.745816e-02 7.793299e-01 1.919058e-02 8.519479e-01 3.598121e-01
#> [96] 8.082333e-01 9.397125e-01 7.366879e-02 9.695916e-01 5.469545e-01
#> [101] 2.298184e-01 7.511952e-01 6.808006e-01 9.100979e-01 7.081412e-04
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 134 8 8.1 86 125 97 181 39 127 91 117 92 171
#> 17.81 18.43 18.43 23.81 15.65 19.14 16.46 15.59 3.53 5.33 17.46 22.92 16.57
#> 15 40 88 29 90 76 58 57 113 188 14 97.1 26
#> 22.68 18.00 18.37 15.45 20.94 19.22 19.34 14.46 22.86 16.16 12.89 19.14 15.77
#> 66 68 187 100 99 43 108 106 51 96 194 150 105
#> 22.13 20.62 9.92 16.07 21.19 12.10 18.29 16.67 18.23 14.54 22.40 20.33 19.75
#> 110 168 36 184 40.1 106.1 164 16 57.1 197 117.1 169 111
#> 17.56 23.72 21.19 17.77 18.00 16.67 23.60 8.71 14.46 21.60 17.46 22.41 17.45
#> 113.1 134.1 58.1 154 40.2 157 194.1 184.1 85 150.1 14.1 86.1 187.1
#> 22.86 17.81 19.34 12.63 18.00 15.10 22.40 17.77 16.44 20.33 12.89 23.81 9.92
#> 99.1 150.2 60 6 15.1 158 51.1 101 57.2 32 130 68.1 140
#> 21.19 20.33 13.15 15.64 22.68 20.14 18.23 9.97 14.46 20.90 16.47 20.62 12.68
#> 157.1 32.1 164.1 86.2 128 180 188.1 14.2 133 78 70 101.1 136
#> 15.10 20.90 23.60 23.81 20.35 14.82 16.16 12.89 14.65 23.88 7.38 9.97 21.83
#> 177 63 187.2 111.1 52 91.1 90.1 127.1 157.2 51.2 154.1 155 149
#> 12.53 22.77 9.92 17.45 10.42 5.33 20.94 3.53 15.10 18.23 12.63 13.08 8.37
#> 86.3 72 87 156 9 84 95 2 178 112 200 53 46
#> 23.81 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87.1 7 1 34 163 2.1 163.1 121 94 116 120 67 9.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 193 143 27 84.1 191 156.1 27.1 144 75 103 17 185
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103.1 120.1 67.1 120.2 83 7.1 182 7.2 151 9.2 196 67.2 193.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 64 28 46.1 185.1 103.2 74 120.3 71 146 21.1 122 53.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75.1 28.1 12 17.1 19 132 196.1 109 121.1 87.2 20 35 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146.1 38.1 80 65 54 34.1 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[33]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.008366113 0.452008919 0.461424913
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.06626012 0.02207919 0.07907193
#> grade_iii, Cure model
#> 0.53833615
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 108 18.29 1 39 0 1
#> 61 10.12 1 36 0 1
#> 167 15.55 1 56 1 0
#> 88 18.37 1 47 0 0
#> 26 15.77 1 49 0 1
#> 6 15.64 1 39 0 0
#> 164 23.60 1 76 0 1
#> 113 22.86 1 34 0 0
#> 195 11.76 1 NA 1 0
#> 32 20.90 1 37 1 0
#> 188 16.16 1 46 0 1
#> 187 9.92 1 39 1 0
#> 159 10.55 1 50 0 1
#> 78 23.88 1 43 0 0
#> 189 10.51 1 NA 1 0
#> 153 21.33 1 55 1 0
#> 106 16.67 1 49 1 0
#> 60 13.15 1 38 1 0
#> 69 23.23 1 25 0 1
#> 145 10.07 1 65 1 0
#> 81 14.06 1 34 0 0
#> 190 20.81 1 42 1 0
#> 61.1 10.12 1 36 0 1
#> 76 19.22 1 54 0 1
#> 192 16.44 1 31 1 0
#> 110 17.56 1 65 0 1
#> 168 23.72 1 70 0 0
#> 39 15.59 1 37 0 1
#> 81.1 14.06 1 34 0 0
#> 133 14.65 1 57 0 0
#> 52 10.42 1 52 0 1
#> 168.1 23.72 1 70 0 0
#> 63 22.77 1 31 1 0
#> 117 17.46 1 26 0 1
#> 158 20.14 1 74 1 0
#> 171 16.57 1 41 0 1
#> 5 16.43 1 51 0 1
#> 52.1 10.42 1 52 0 1
#> 6.1 15.64 1 39 0 0
#> 105 19.75 1 60 0 0
#> 61.2 10.12 1 36 0 1
#> 189.1 10.51 1 NA 1 0
#> 89 11.44 1 NA 0 0
#> 181 16.46 1 45 0 1
#> 26.1 15.77 1 49 0 1
#> 68 20.62 1 44 0 0
#> 78.1 23.88 1 43 0 0
#> 93 10.33 1 52 0 1
#> 51 18.23 1 83 0 1
#> 79 16.23 1 54 1 0
#> 10 10.53 1 34 0 0
#> 123 13.00 1 44 1 0
#> 197 21.60 1 69 1 0
#> 114 13.68 1 NA 0 0
#> 88.1 18.37 1 47 0 0
#> 170 19.54 1 43 0 1
#> 150 20.33 1 48 0 0
#> 164.1 23.60 1 76 0 1
#> 99 21.19 1 38 0 1
#> 183 9.24 1 67 1 0
#> 199 19.81 1 NA 0 1
#> 79.1 16.23 1 54 1 0
#> 32.1 20.90 1 37 1 0
#> 134 17.81 1 47 1 0
#> 179 18.63 1 42 0 0
#> 57 14.46 1 45 0 1
#> 26.2 15.77 1 49 0 1
#> 8 18.43 1 32 0 0
#> 177 12.53 1 75 0 0
#> 167.1 15.55 1 56 1 0
#> 130 16.47 1 53 0 1
#> 61.3 10.12 1 36 0 1
#> 58 19.34 1 39 0 0
#> 192.1 16.44 1 31 1 0
#> 23 16.92 1 61 0 0
#> 42 12.43 1 49 0 1
#> 123.1 13.00 1 44 1 0
#> 70 7.38 1 30 1 0
#> 155 13.08 1 26 0 0
#> 13 14.34 1 54 0 1
#> 26.3 15.77 1 49 0 1
#> 140 12.68 1 59 1 0
#> 114.1 13.68 1 NA 0 0
#> 113.1 22.86 1 34 0 0
#> 123.2 13.00 1 44 1 0
#> 86 23.81 1 58 0 1
#> 60.1 13.15 1 38 1 0
#> 124 9.73 1 NA 1 0
#> 114.2 13.68 1 NA 0 0
#> 66 22.13 1 53 0 0
#> 51.1 18.23 1 83 0 1
#> 29 15.45 1 68 1 0
#> 129 23.41 1 53 1 0
#> 184 17.77 1 38 0 0
#> 155.1 13.08 1 26 0 0
#> 110.1 17.56 1 65 0 1
#> 63.1 22.77 1 31 1 0
#> 43 12.10 1 61 0 1
#> 189.2 10.51 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 68.1 20.62 1 44 0 0
#> 50 10.02 1 NA 1 0
#> 157 15.10 1 47 0 0
#> 157.1 15.10 1 47 0 0
#> 114.3 13.68 1 NA 0 0
#> 105.1 19.75 1 60 0 0
#> 37 12.52 1 57 1 0
#> 130.1 16.47 1 53 0 1
#> 133.1 14.65 1 57 0 0
#> 158.1 20.14 1 74 1 0
#> 194 22.40 1 38 0 1
#> 45 17.42 1 54 0 1
#> 65 24.00 0 57 1 0
#> 53 24.00 0 32 0 1
#> 71 24.00 0 51 0 0
#> 103 24.00 0 56 1 0
#> 178 24.00 0 52 1 0
#> 94 24.00 0 51 0 1
#> 119 24.00 0 17 0 0
#> 3 24.00 0 31 1 0
#> 74 24.00 0 43 0 1
#> 109 24.00 0 48 0 0
#> 95 24.00 0 68 0 1
#> 162 24.00 0 51 0 0
#> 87 24.00 0 27 0 0
#> 196 24.00 0 19 0 0
#> 17 24.00 0 38 0 1
#> 67 24.00 0 25 0 0
#> 109.1 24.00 0 48 0 0
#> 143 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 75 24.00 0 21 1 0
#> 83 24.00 0 6 0 0
#> 103.1 24.00 0 56 1 0
#> 75.1 24.00 0 21 1 0
#> 84 24.00 0 39 0 1
#> 94.1 24.00 0 51 0 1
#> 156 24.00 0 50 1 0
#> 44 24.00 0 56 0 0
#> 34 24.00 0 36 0 0
#> 73 24.00 0 NA 0 1
#> 94.2 24.00 0 51 0 1
#> 75.2 24.00 0 21 1 0
#> 122 24.00 0 66 0 0
#> 19 24.00 0 57 0 1
#> 48 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 135 24.00 0 58 1 0
#> 138 24.00 0 44 1 0
#> 151 24.00 0 42 0 0
#> 95.1 24.00 0 68 0 1
#> 19.1 24.00 0 57 0 1
#> 144 24.00 0 28 0 1
#> 126 24.00 0 48 0 0
#> 151.1 24.00 0 42 0 0
#> 53.1 24.00 0 32 0 1
#> 196.1 24.00 0 19 0 0
#> 178.1 24.00 0 52 1 0
#> 191 24.00 0 60 0 1
#> 200 24.00 0 64 0 0
#> 151.2 24.00 0 42 0 0
#> 33 24.00 0 53 0 0
#> 132 24.00 0 55 0 0
#> 80 24.00 0 41 0 0
#> 178.2 24.00 0 52 1 0
#> 120 24.00 0 68 0 1
#> 173 24.00 0 19 0 1
#> 121 24.00 0 57 1 0
#> 1 24.00 0 23 1 0
#> 34.1 24.00 0 36 0 0
#> 115 24.00 0 NA 1 0
#> 161 24.00 0 45 0 0
#> 102 24.00 0 49 0 0
#> 1.1 24.00 0 23 1 0
#> 160 24.00 0 31 1 0
#> 74.1 24.00 0 43 0 1
#> 84.1 24.00 0 39 0 1
#> 87.1 24.00 0 27 0 0
#> 162.1 24.00 0 51 0 0
#> 71.1 24.00 0 51 0 0
#> 151.3 24.00 0 42 0 0
#> 62 24.00 0 71 0 0
#> 109.2 24.00 0 48 0 0
#> 144.1 24.00 0 28 0 1
#> 22.1 24.00 0 52 1 0
#> 48.1 24.00 0 31 1 0
#> 65.1 24.00 0 57 1 0
#> 143.1 24.00 0 51 0 0
#> 38 24.00 0 31 1 0
#> 65.2 24.00 0 57 1 0
#> 148 24.00 0 61 1 0
#> 121.1 24.00 0 57 1 0
#> 109.3 24.00 0 48 0 0
#> 2 24.00 0 9 0 0
#> 20 24.00 0 46 1 0
#> 94.3 24.00 0 51 0 1
#> 191.1 24.00 0 60 0 1
#> 186 24.00 0 45 1 0
#> 95.2 24.00 0 68 0 1
#> 34.2 24.00 0 36 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.07 NA NA NA
#> 2 age, Cure model 0.0221 NA NA NA
#> 3 grade_ii, Cure model 0.0791 NA NA NA
#> 4 grade_iii, Cure model 0.538 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00837 NA NA NA
#> 2 grade_ii, Survival model 0.452 NA NA NA
#> 3 grade_iii, Survival model 0.461 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.06626 0.02208 0.07907 0.53834
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.8
#> Residual Deviance: 249.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.06626012 0.02207919 0.07907193 0.53833615
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.008366113 0.452008919 0.461424913
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.31776074 0.91515766 0.61739694 0.29742538 0.54593565 0.58625519
#> [7] 0.03689593 0.07305890 0.15518042 0.52518862 0.96793225 0.86133244
#> [13] 0.00325377 0.13652730 0.42160309 0.73327354 0.06389489 0.95722661
#> [19] 0.71195767 0.17287499 0.91515766 0.26734236 0.47383132 0.36943573
#> [25] 0.02078700 0.60697600 0.71195767 0.66945159 0.88290599 0.02078700
#> [31] 0.09131630 0.39018514 0.20952110 0.43213489 0.49433812 0.88290599
#> [37] 0.58625519 0.22823868 0.91515766 0.46336730 0.54593565 0.18191089
#> [43] 0.00325377 0.90436645 0.32804814 0.50469246 0.87210270 0.77584570
#> [49] 0.12716032 0.29742538 0.24758290 0.20007682 0.03689593 0.14589974
#> [55] 0.97862206 0.50469246 0.15518042 0.34856384 0.27727135 0.69063751
#> [61] 0.54593565 0.28730684 0.81823605 0.61739694 0.44263455 0.91515766
#> [67] 0.25740983 0.47383132 0.41105998 0.83978657 0.77584570 0.98932388
#> [73] 0.75450091 0.70129837 0.54593565 0.80752823 0.07305890 0.77584570
#> [79] 0.01363684 0.73327354 0.11787413 0.32804814 0.63807431 0.05434087
#> [85] 0.35895847 0.75450091 0.36943573 0.09131630 0.85055625 0.53552248
#> [91] 0.18191089 0.64851697 0.64851697 0.22823868 0.82900959 0.44263455
#> [97] 0.66945159 0.20952110 0.10884299 0.40062387 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 108 61 167 88 26 6 164 113 32 188 187 159 78
#> 18.29 10.12 15.55 18.37 15.77 15.64 23.60 22.86 20.90 16.16 9.92 10.55 23.88
#> 153 106 60 69 145 81 190 61.1 76 192 110 168 39
#> 21.33 16.67 13.15 23.23 10.07 14.06 20.81 10.12 19.22 16.44 17.56 23.72 15.59
#> 81.1 133 52 168.1 63 117 158 171 5 52.1 6.1 105 61.2
#> 14.06 14.65 10.42 23.72 22.77 17.46 20.14 16.57 16.43 10.42 15.64 19.75 10.12
#> 181 26.1 68 78.1 93 51 79 10 123 197 88.1 170 150
#> 16.46 15.77 20.62 23.88 10.33 18.23 16.23 10.53 13.00 21.60 18.37 19.54 20.33
#> 164.1 99 183 79.1 32.1 134 179 57 26.2 8 177 167.1 130
#> 23.60 21.19 9.24 16.23 20.90 17.81 18.63 14.46 15.77 18.43 12.53 15.55 16.47
#> 61.3 58 192.1 23 42 123.1 70 155 13 26.3 140 113.1 123.2
#> 10.12 19.34 16.44 16.92 12.43 13.00 7.38 13.08 14.34 15.77 12.68 22.86 13.00
#> 86 60.1 66 51.1 29 129 184 155.1 110.1 63.1 43 100 68.1
#> 23.81 13.15 22.13 18.23 15.45 23.41 17.77 13.08 17.56 22.77 12.10 16.07 20.62
#> 157 157.1 105.1 37 130.1 133.1 158.1 194 45 65 53 71 103
#> 15.10 15.10 19.75 12.52 16.47 14.65 20.14 22.40 17.42 24.00 24.00 24.00 24.00
#> 178 94 119 3 74 109 95 162 87 196 17 67 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 22 75 83 103.1 75.1 84 94.1 156 44 34 94.2 75.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 19 48 9 135 138 151 95.1 19.1 144 126 151.1 53.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196.1 178.1 191 200 151.2 33 132 80 178.2 120 173 121 1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34.1 161 102 1.1 160 74.1 84.1 87.1 162.1 71.1 151.3 62 109.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144.1 22.1 48.1 65.1 143.1 38 65.2 148 121.1 109.3 2 20 94.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191.1 186 95.2 34.2
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[34]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01055229 0.56666263 0.28285822
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.68319162 0.01980269 0.59311247
#> grade_iii, Cure model
#> 2.34165806
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 189 10.51 1 NA 1 0
#> 199 19.81 1 NA 0 1
#> 5 16.43 1 51 0 1
#> 150 20.33 1 48 0 0
#> 70 7.38 1 30 1 0
#> 110 17.56 1 65 0 1
#> 189.1 10.51 1 NA 1 0
#> 90 20.94 1 50 0 1
#> 37 12.52 1 57 1 0
#> 55 19.34 1 69 0 1
#> 100 16.07 1 60 0 0
#> 117 17.46 1 26 0 1
#> 56 12.21 1 60 0 0
#> 130 16.47 1 53 0 1
#> 192 16.44 1 31 1 0
#> 180 14.82 1 37 0 0
#> 197 21.60 1 69 1 0
#> 183 9.24 1 67 1 0
#> 36 21.19 1 48 0 1
#> 105 19.75 1 60 0 0
#> 55.1 19.34 1 69 0 1
#> 101 9.97 1 10 0 1
#> 37.1 12.52 1 57 1 0
#> 167 15.55 1 56 1 0
#> 36.1 21.19 1 48 0 1
#> 90.1 20.94 1 50 0 1
#> 70.1 7.38 1 30 1 0
#> 77 7.27 1 67 0 1
#> 140 12.68 1 59 1 0
#> 70.2 7.38 1 30 1 0
#> 153 21.33 1 55 1 0
#> 55.2 19.34 1 69 0 1
#> 140.1 12.68 1 59 1 0
#> 86 23.81 1 58 0 1
#> 50 10.02 1 NA 1 0
#> 41 18.02 1 40 1 0
#> 37.2 12.52 1 57 1 0
#> 159 10.55 1 50 0 1
#> 197.1 21.60 1 69 1 0
#> 167.1 15.55 1 56 1 0
#> 171 16.57 1 41 0 1
#> 60 13.15 1 38 1 0
#> 69 23.23 1 25 0 1
#> 60.1 13.15 1 38 1 0
#> 63 22.77 1 31 1 0
#> 123 13.00 1 44 1 0
#> 117.1 17.46 1 26 0 1
#> 77.1 7.27 1 67 0 1
#> 52 10.42 1 52 0 1
#> 124 9.73 1 NA 1 0
#> 77.2 7.27 1 67 0 1
#> 105.1 19.75 1 60 0 0
#> 23 16.92 1 61 0 0
#> 197.2 21.60 1 69 1 0
#> 194 22.40 1 38 0 1
#> 68 20.62 1 44 0 0
#> 93 10.33 1 52 0 1
#> 164 23.60 1 76 0 1
#> 181 16.46 1 45 0 1
#> 194.1 22.40 1 38 0 1
#> 96 14.54 1 33 0 1
#> 96.1 14.54 1 33 0 1
#> 139 21.49 1 63 1 0
#> 63.1 22.77 1 31 1 0
#> 130.1 16.47 1 53 0 1
#> 110.1 17.56 1 65 0 1
#> 93.1 10.33 1 52 0 1
#> 26 15.77 1 49 0 1
#> 167.2 15.55 1 56 1 0
#> 113 22.86 1 34 0 0
#> 52.1 10.42 1 52 0 1
#> 114 13.68 1 NA 0 0
#> 159.1 10.55 1 50 0 1
#> 114.1 13.68 1 NA 0 0
#> 124.1 9.73 1 NA 1 0
#> 133 14.65 1 57 0 0
#> 164.1 23.60 1 76 0 1
#> 187 9.92 1 39 1 0
#> 181.1 16.46 1 45 0 1
#> 78 23.88 1 43 0 0
#> 183.1 9.24 1 67 1 0
#> 181.2 16.46 1 45 0 1
#> 8 18.43 1 32 0 0
#> 106 16.67 1 49 1 0
#> 50.1 10.02 1 NA 1 0
#> 14 12.89 1 21 0 0
#> 199.1 19.81 1 NA 0 1
#> 43 12.10 1 61 0 1
#> 88 18.37 1 47 0 0
#> 66 22.13 1 53 0 0
#> 77.3 7.27 1 67 0 1
#> 58 19.34 1 39 0 0
#> 4 17.64 1 NA 0 1
#> 108 18.29 1 39 0 1
#> 52.2 10.42 1 52 0 1
#> 164.2 23.60 1 76 0 1
#> 154 12.63 1 20 1 0
#> 155 13.08 1 26 0 0
#> 159.2 10.55 1 50 0 1
#> 36.2 21.19 1 48 0 1
#> 61 10.12 1 36 0 1
#> 50.2 10.02 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 175 21.91 1 43 0 0
#> 8.1 18.43 1 32 0 0
#> 50.3 10.02 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 133.1 14.65 1 57 0 0
#> 68.1 20.62 1 44 0 0
#> 42 12.43 1 49 0 1
#> 164.3 23.60 1 76 0 1
#> 39 15.59 1 37 0 1
#> 22 24.00 0 52 1 0
#> 33 24.00 0 53 0 0
#> 103 24.00 0 56 1 0
#> 142 24.00 0 53 0 0
#> 34 24.00 0 36 0 0
#> 174 24.00 0 49 1 0
#> 38 24.00 0 31 1 0
#> 121 24.00 0 57 1 0
#> 185 24.00 0 44 1 0
#> 193 24.00 0 45 0 1
#> 196 24.00 0 19 0 0
#> 174.1 24.00 0 49 1 0
#> 146 24.00 0 63 1 0
#> 141 24.00 0 44 1 0
#> 161 24.00 0 45 0 0
#> 46 24.00 0 71 0 0
#> 200 24.00 0 64 0 0
#> 126 24.00 0 48 0 0
#> 12 24.00 0 63 0 0
#> 200.1 24.00 0 64 0 0
#> 72 24.00 0 40 0 1
#> 67 24.00 0 25 0 0
#> 191 24.00 0 60 0 1
#> 2 24.00 0 9 0 0
#> 65 24.00 0 57 1 0
#> 146.1 24.00 0 63 1 0
#> 144 24.00 0 28 0 1
#> 137 24.00 0 45 1 0
#> 38.1 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 143 24.00 0 51 0 0
#> 20 24.00 0 46 1 0
#> 34.1 24.00 0 36 0 0
#> 132 24.00 0 55 0 0
#> 156 24.00 0 50 1 0
#> 7 24.00 0 37 1 0
#> 82 24.00 0 34 0 0
#> 138 24.00 0 44 1 0
#> 48 24.00 0 31 1 0
#> 22.1 24.00 0 52 1 0
#> 82.1 24.00 0 34 0 0
#> 126.1 24.00 0 48 0 0
#> 44 24.00 0 56 0 0
#> 165 24.00 0 47 0 0
#> 200.2 24.00 0 64 0 0
#> 12.1 24.00 0 63 0 0
#> 38.2 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 12.2 24.00 0 63 0 0
#> 38.3 24.00 0 31 1 0
#> 182 24.00 0 35 0 0
#> 146.2 24.00 0 63 1 0
#> 131 24.00 0 66 0 0
#> 98 24.00 0 34 1 0
#> 142.1 24.00 0 53 0 0
#> 103.1 24.00 0 56 1 0
#> 21 24.00 0 47 0 0
#> 82.2 24.00 0 34 0 0
#> 103.2 24.00 0 56 1 0
#> 119.1 24.00 0 17 0 0
#> 67.1 24.00 0 25 0 0
#> 185.1 24.00 0 44 1 0
#> 131.1 24.00 0 66 0 0
#> 1.1 24.00 0 23 1 0
#> 84 24.00 0 39 0 1
#> 142.2 24.00 0 53 0 0
#> 2.1 24.00 0 9 0 0
#> 176 24.00 0 43 0 1
#> 144.1 24.00 0 28 0 1
#> 200.3 24.00 0 64 0 0
#> 182.1 24.00 0 35 0 0
#> 80 24.00 0 41 0 0
#> 11 24.00 0 42 0 1
#> 152 24.00 0 36 0 1
#> 1.2 24.00 0 23 1 0
#> 71 24.00 0 51 0 0
#> 143.1 24.00 0 51 0 0
#> 48.1 24.00 0 31 1 0
#> 146.3 24.00 0 63 1 0
#> 142.3 24.00 0 53 0 0
#> 119.2 24.00 0 17 0 0
#> 33.1 24.00 0 53 0 0
#> 118 24.00 0 44 1 0
#> 21.1 24.00 0 47 0 0
#> 109 24.00 0 48 0 0
#> 46.1 24.00 0 71 0 0
#> 178 24.00 0 52 1 0
#> 176.1 24.00 0 43 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.68 NA NA NA
#> 2 age, Cure model 0.0198 NA NA NA
#> 3 grade_ii, Cure model 0.593 NA NA NA
#> 4 grade_iii, Cure model 2.34 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0106 NA NA NA
#> 2 grade_ii, Survival model 0.567 NA NA NA
#> 3 grade_iii, Survival model 0.283 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.6832 0.0198 0.5931 2.3417
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258.6
#> Residual Deviance: 217.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.68319162 0.01980269 0.59311247 2.34165806
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01055229 0.56666263 0.28285822
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.455374000 0.198492526 0.905329370 0.316049242 0.163828580 0.682482261
#> [7] 0.226422218 0.466443134 0.337010654 0.728061561 0.390328186 0.444365172
#> [13] 0.533283226 0.099729554 0.881470120 0.139504327 0.207684239 0.226422218
#> [19] 0.857504946 0.682482261 0.500160949 0.139504327 0.163828580 0.905329370
#> [25] 0.940489302 0.647974585 0.905329370 0.131186516 0.226422218 0.647974585
#> [31] 0.005324833 0.305622312 0.682482261 0.751415353 0.099729554 0.500160949
#> [37] 0.379516113 0.590498853 0.032507968 0.590498853 0.048193371 0.624858840
#> [43] 0.337010654 0.940489302 0.786334666 0.940489302 0.207684239 0.357961368
#> [49] 0.099729554 0.061893043 0.180851780 0.821619987 0.011139745 0.411938182
#> [55] 0.061893043 0.567539267 0.567539267 0.122876057 0.048193371 0.390328186
#> [61] 0.316049242 0.821619987 0.477636880 0.500160949 0.040118053 0.786334666
#> [67] 0.751415353 0.544638421 0.011139745 0.869501386 0.411938182 0.001103161
#> [73] 0.881470120 0.411938182 0.264493634 0.368746737 0.636395849 0.739710539
#> [79] 0.284702074 0.075951182 0.940489302 0.226422218 0.295139795 0.786334666
#> [85] 0.011139745 0.670969532 0.613298832 0.751415353 0.139504327 0.845475857
#> [91] 0.091639900 0.083661267 0.264493634 0.987886509 0.544638421 0.180851780
#> [97] 0.716499362 0.011139745 0.488885679 0.000000000 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 5 150 70 110 90 37 55 100 117 56 130 192 180
#> 16.43 20.33 7.38 17.56 20.94 12.52 19.34 16.07 17.46 12.21 16.47 16.44 14.82
#> 197 183 36 105 55.1 101 37.1 167 36.1 90.1 70.1 77 140
#> 21.60 9.24 21.19 19.75 19.34 9.97 12.52 15.55 21.19 20.94 7.38 7.27 12.68
#> 70.2 153 55.2 140.1 86 41 37.2 159 197.1 167.1 171 60 69
#> 7.38 21.33 19.34 12.68 23.81 18.02 12.52 10.55 21.60 15.55 16.57 13.15 23.23
#> 60.1 63 123 117.1 77.1 52 77.2 105.1 23 197.2 194 68 93
#> 13.15 22.77 13.00 17.46 7.27 10.42 7.27 19.75 16.92 21.60 22.40 20.62 10.33
#> 164 181 194.1 96 96.1 139 63.1 130.1 110.1 93.1 26 167.2 113
#> 23.60 16.46 22.40 14.54 14.54 21.49 22.77 16.47 17.56 10.33 15.77 15.55 22.86
#> 52.1 159.1 133 164.1 187 181.1 78 183.1 181.2 8 106 14 43
#> 10.42 10.55 14.65 23.60 9.92 16.46 23.88 9.24 16.46 18.43 16.67 12.89 12.10
#> 88 66 77.3 58 108 52.2 164.2 154 155 159.2 36.2 61 136
#> 18.37 22.13 7.27 19.34 18.29 10.42 23.60 12.63 13.08 10.55 21.19 10.12 21.83
#> 175 8.1 91 133.1 68.1 42 164.3 39 22 33 103 142 34
#> 21.91 18.43 5.33 14.65 20.62 12.43 23.60 15.59 24.00 24.00 24.00 24.00 24.00
#> 174 38 121 185 193 196 174.1 146 141 161 46 200 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 200.1 72 67 191 2 65 146.1 144 137 38.1 119 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 34.1 132 156 7 82 138 48 22.1 82.1 126.1 44 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200.2 12.1 38.2 1 12.2 38.3 182 146.2 131 98 142.1 103.1 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82.2 103.2 119.1 67.1 185.1 131.1 1.1 84 142.2 2.1 176 144.1 200.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182.1 80 11 152 1.2 71 143.1 48.1 146.3 142.3 119.2 33.1 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21.1 109 46.1 178 176.1
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[35]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001897636 0.168587304 0.181698572
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.500056830 -0.008536272 -0.150535446
#> grade_iii, Cure model
#> 0.402582541
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 36 21.19 1 48 0 1
#> 59 10.16 1 NA 1 0
#> 125 15.65 1 67 1 0
#> 58 19.34 1 39 0 0
#> 155 13.08 1 26 0 0
#> 134 17.81 1 47 1 0
#> 18 15.21 1 49 1 0
#> 93 10.33 1 52 0 1
#> 76 19.22 1 54 0 1
#> 190 20.81 1 42 1 0
#> 111 17.45 1 47 0 1
#> 93.1 10.33 1 52 0 1
#> 63 22.77 1 31 1 0
#> 99 21.19 1 38 0 1
#> 180 14.82 1 37 0 0
#> 78 23.88 1 43 0 0
#> 81 14.06 1 34 0 0
#> 30 17.43 1 78 0 0
#> 190.1 20.81 1 42 1 0
#> 149 8.37 1 33 1 0
#> 77 7.27 1 67 0 1
#> 190.2 20.81 1 42 1 0
#> 30.1 17.43 1 78 0 0
#> 89 11.44 1 NA 0 0
#> 93.2 10.33 1 52 0 1
#> 159 10.55 1 50 0 1
#> 108 18.29 1 39 0 1
#> 60 13.15 1 38 1 0
#> 52 10.42 1 52 0 1
#> 51 18.23 1 83 0 1
#> 23 16.92 1 61 0 0
#> 14 12.89 1 21 0 0
#> 42 12.43 1 49 0 1
#> 68 20.62 1 44 0 0
#> 153 21.33 1 55 1 0
#> 69 23.23 1 25 0 1
#> 76.1 19.22 1 54 0 1
#> 139 21.49 1 63 1 0
#> 45 17.42 1 54 0 1
#> 49 12.19 1 48 1 0
#> 133 14.65 1 57 0 0
#> 59.1 10.16 1 NA 1 0
#> 43 12.10 1 61 0 1
#> 183 9.24 1 67 1 0
#> 39 15.59 1 37 0 1
#> 97 19.14 1 65 0 1
#> 29 15.45 1 68 1 0
#> 61 10.12 1 36 0 1
#> 197 21.60 1 69 1 0
#> 192 16.44 1 31 1 0
#> 170 19.54 1 43 0 1
#> 110 17.56 1 65 0 1
#> 192.1 16.44 1 31 1 0
#> 41 18.02 1 40 1 0
#> 199 19.81 1 NA 0 1
#> 23.1 16.92 1 61 0 0
#> 26 15.77 1 49 0 1
#> 130 16.47 1 53 0 1
#> 59.2 10.16 1 NA 1 0
#> 164 23.60 1 76 0 1
#> 77.1 7.27 1 67 0 1
#> 106 16.67 1 49 1 0
#> 14.1 12.89 1 21 0 0
#> 89.1 11.44 1 NA 0 0
#> 89.2 11.44 1 NA 0 0
#> 58.1 19.34 1 39 0 0
#> 130.1 16.47 1 53 0 1
#> 36.1 21.19 1 48 0 1
#> 169 22.41 1 46 0 0
#> 16 8.71 1 71 0 1
#> 155.1 13.08 1 26 0 0
#> 91 5.33 1 61 0 1
#> 184 17.77 1 38 0 0
#> 192.2 16.44 1 31 1 0
#> 128 20.35 1 35 0 1
#> 69.1 23.23 1 25 0 1
#> 155.2 13.08 1 26 0 0
#> 96 14.54 1 33 0 1
#> 14.2 12.89 1 21 0 0
#> 61.1 10.12 1 36 0 1
#> 30.2 17.43 1 78 0 0
#> 8 18.43 1 32 0 0
#> 76.2 19.22 1 54 0 1
#> 179 18.63 1 42 0 0
#> 106.1 16.67 1 49 1 0
#> 61.2 10.12 1 36 0 1
#> 106.2 16.67 1 49 1 0
#> 88 18.37 1 47 0 0
#> 124 9.73 1 NA 1 0
#> 25 6.32 1 34 1 0
#> 171 16.57 1 41 0 1
#> 184.1 17.77 1 38 0 0
#> 150 20.33 1 48 0 0
#> 97.1 19.14 1 65 0 1
#> 184.2 17.77 1 38 0 0
#> 42.1 12.43 1 49 0 1
#> 81.1 14.06 1 34 0 0
#> 199.1 19.81 1 NA 0 1
#> 183.1 9.24 1 67 1 0
#> 49.1 12.19 1 48 1 0
#> 189 10.51 1 NA 1 0
#> 110.1 17.56 1 65 0 1
#> 24 23.89 1 38 0 0
#> 179.1 18.63 1 42 0 0
#> 154 12.63 1 20 1 0
#> 30.3 17.43 1 78 0 0
#> 16.1 8.71 1 71 0 1
#> 81.2 14.06 1 34 0 0
#> 117 17.46 1 26 0 1
#> 190.3 20.81 1 42 1 0
#> 187 9.92 1 39 1 0
#> 76.3 19.22 1 54 0 1
#> 131 24.00 0 66 0 0
#> 53 24.00 0 32 0 1
#> 80 24.00 0 41 0 0
#> 138 24.00 0 44 1 0
#> 198 24.00 0 66 0 1
#> 191 24.00 0 60 0 1
#> 161 24.00 0 45 0 0
#> 80.1 24.00 0 41 0 0
#> 11 24.00 0 42 0 1
#> 118 24.00 0 44 1 0
#> 144 24.00 0 28 0 1
#> 73 24.00 0 NA 0 1
#> 176 24.00 0 43 0 1
#> 126 24.00 0 48 0 0
#> 144.1 24.00 0 28 0 1
#> 162 24.00 0 51 0 0
#> 95 24.00 0 68 0 1
#> 132 24.00 0 55 0 0
#> 115 24.00 0 NA 1 0
#> 20 24.00 0 46 1 0
#> 191.1 24.00 0 60 0 1
#> 137 24.00 0 45 1 0
#> 9 24.00 0 31 1 0
#> 144.2 24.00 0 28 0 1
#> 186 24.00 0 45 1 0
#> 35 24.00 0 51 0 0
#> 35.1 24.00 0 51 0 0
#> 186.1 24.00 0 45 1 0
#> 142 24.00 0 53 0 0
#> 131.1 24.00 0 66 0 0
#> 112 24.00 0 61 0 0
#> 44 24.00 0 56 0 0
#> 132.1 24.00 0 55 0 0
#> 3 24.00 0 31 1 0
#> 196 24.00 0 19 0 0
#> 198.1 24.00 0 66 0 1
#> 72 24.00 0 40 0 1
#> 148 24.00 0 61 1 0
#> 19 24.00 0 57 0 1
#> 9.1 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 44.1 24.00 0 56 0 0
#> 119 24.00 0 17 0 0
#> 34 24.00 0 36 0 0
#> 120 24.00 0 68 0 1
#> 19.1 24.00 0 57 0 1
#> 17 24.00 0 38 0 1
#> 12 24.00 0 63 0 0
#> 75 24.00 0 21 1 0
#> 19.2 24.00 0 57 0 1
#> 3.1 24.00 0 31 1 0
#> 12.1 24.00 0 63 0 0
#> 121 24.00 0 57 1 0
#> 200 24.00 0 64 0 0
#> 146 24.00 0 63 1 0
#> 116 24.00 0 58 0 1
#> 22 24.00 0 52 1 0
#> 165 24.00 0 47 0 0
#> 34.1 24.00 0 36 0 0
#> 137.1 24.00 0 45 1 0
#> 141 24.00 0 44 1 0
#> 115.1 24.00 0 NA 1 0
#> 126.1 24.00 0 48 0 0
#> 142.1 24.00 0 53 0 0
#> 121.1 24.00 0 57 1 0
#> 95.1 24.00 0 68 0 1
#> 9.2 24.00 0 31 1 0
#> 9.3 24.00 0 31 1 0
#> 160 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 148.1 24.00 0 61 1 0
#> 120.1 24.00 0 68 0 1
#> 103 24.00 0 56 1 0
#> 62 24.00 0 71 0 0
#> 160.1 24.00 0 31 1 0
#> 115.2 24.00 0 NA 1 0
#> 94 24.00 0 51 0 1
#> 146.1 24.00 0 63 1 0
#> 72.1 24.00 0 40 0 1
#> 137.2 24.00 0 45 1 0
#> 176.1 24.00 0 43 0 1
#> 160.2 24.00 0 31 1 0
#> 198.2 24.00 0 66 0 1
#> 198.3 24.00 0 66 0 1
#> 84 24.00 0 39 0 1
#> 193 24.00 0 45 0 1
#> 172 24.00 0 41 0 0
#> 54 24.00 0 53 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.500 NA NA NA
#> 2 age, Cure model -0.00854 NA NA NA
#> 3 grade_ii, Cure model -0.151 NA NA NA
#> 4 grade_iii, Cure model 0.403 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00190 NA NA NA
#> 2 grade_ii, Survival model 0.169 NA NA NA
#> 3 grade_iii, Survival model 0.182 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.500057 -0.008536 -0.150535 0.402583
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.1
#> Residual Deviance: 253.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.500056830 -0.008536272 -0.150535446 0.402582541
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001897636 0.168587304 0.181698572
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.16892725 0.66232375 0.28843104 0.75600198 0.43683833 0.68820380
#> [7] 0.87240589 0.30950146 0.20301771 0.50250393 0.87240589 0.09953639
#> [13] 0.16892725 0.69676270 0.03396772 0.72236465 0.51181087 0.20301771
#> [19] 0.96056624 0.96851461 0.20301771 0.51181087 0.87240589 0.85592939
#> [25] 0.40762387 0.74754025 0.86418035 0.41744394 0.55676564 0.78106209
#> [31] 0.81449983 0.24464250 0.15584268 0.07155723 0.30950146 0.14240491
#> [37] 0.54763220 0.83112543 0.70531396 0.84765301 0.92873652 0.67098430
#> [43] 0.34853029 0.67961295 0.89663099 0.12853131 0.62776345 0.27763470
#> [49] 0.47450795 0.62776345 0.42717161 0.55676564 0.65362405 0.61021671
#> [55] 0.05396943 0.96851461 0.57481069 0.78106209 0.28843104 0.61021671
#> [61] 0.16892725 0.11411649 0.94470127 0.75600198 0.99213734 0.44644256
#> [67] 0.62776345 0.25574347 0.07155723 0.75600198 0.71385339 0.78106209
#> [73] 0.89663099 0.51181087 0.38782194 0.30950146 0.36821946 0.57481069
#> [79] 0.89663099 0.57481069 0.39773439 0.98425303 0.60129509 0.44644256
#> [85] 0.26671047 0.34853029 0.44644256 0.81449983 0.72236465 0.92873652
#> [91] 0.83112543 0.47450795 0.01339635 0.36821946 0.80608963 0.51181087
#> [97] 0.94470127 0.72236465 0.49314306 0.20301771 0.92067163 0.30950146
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 36 125 58 155 134 18 93 76 190 111 93.1 63 99
#> 21.19 15.65 19.34 13.08 17.81 15.21 10.33 19.22 20.81 17.45 10.33 22.77 21.19
#> 180 78 81 30 190.1 149 77 190.2 30.1 93.2 159 108 60
#> 14.82 23.88 14.06 17.43 20.81 8.37 7.27 20.81 17.43 10.33 10.55 18.29 13.15
#> 52 51 23 14 42 68 153 69 76.1 139 45 49 133
#> 10.42 18.23 16.92 12.89 12.43 20.62 21.33 23.23 19.22 21.49 17.42 12.19 14.65
#> 43 183 39 97 29 61 197 192 170 110 192.1 41 23.1
#> 12.10 9.24 15.59 19.14 15.45 10.12 21.60 16.44 19.54 17.56 16.44 18.02 16.92
#> 26 130 164 77.1 106 14.1 58.1 130.1 36.1 169 16 155.1 91
#> 15.77 16.47 23.60 7.27 16.67 12.89 19.34 16.47 21.19 22.41 8.71 13.08 5.33
#> 184 192.2 128 69.1 155.2 96 14.2 61.1 30.2 8 76.2 179 106.1
#> 17.77 16.44 20.35 23.23 13.08 14.54 12.89 10.12 17.43 18.43 19.22 18.63 16.67
#> 61.2 106.2 88 25 171 184.1 150 97.1 184.2 42.1 81.1 183.1 49.1
#> 10.12 16.67 18.37 6.32 16.57 17.77 20.33 19.14 17.77 12.43 14.06 9.24 12.19
#> 110.1 24 179.1 154 30.3 16.1 81.2 117 190.3 187 76.3 131 53
#> 17.56 23.89 18.63 12.63 17.43 8.71 14.06 17.46 20.81 9.92 19.22 24.00 24.00
#> 80 138 198 191 161 80.1 11 118 144 176 126 144.1 162
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 132 20 191.1 137 9 144.2 186 35 35.1 186.1 142 131.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 44 132.1 3 196 198.1 72 148 19 9.1 71 44.1 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 120 19.1 17 12 75 19.2 3.1 12.1 121 200 146 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 165 34.1 137.1 141 126.1 142.1 121.1 95.1 9.2 9.3 160 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148.1 120.1 103 62 160.1 94 146.1 72.1 137.2 176.1 160.2 198.2 198.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 193 172 54
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[36]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003409052 0.668869382 0.285609792
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.40058828 0.01288437 -0.45124768
#> grade_iii, Cure model
#> 0.44087545
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 78 23.88 1 43 0 0
#> 195 11.76 1 NA 1 0
#> 189 10.51 1 NA 1 0
#> 180 14.82 1 37 0 0
#> 171 16.57 1 41 0 1
#> 187 9.92 1 39 1 0
#> 123 13.00 1 44 1 0
#> 154 12.63 1 20 1 0
#> 92 22.92 1 47 0 1
#> 32 20.90 1 37 1 0
#> 93 10.33 1 52 0 1
#> 39 15.59 1 37 0 1
#> 127 3.53 1 62 0 1
#> 145 10.07 1 65 1 0
#> 188 16.16 1 46 0 1
#> 190 20.81 1 42 1 0
#> 194 22.40 1 38 0 1
#> 25 6.32 1 34 1 0
#> 194.1 22.40 1 38 0 1
#> 113 22.86 1 34 0 0
#> 52 10.42 1 52 0 1
#> 88 18.37 1 47 0 0
#> 13 14.34 1 54 0 1
#> 37 12.52 1 57 1 0
#> 81 14.06 1 34 0 0
#> 32.1 20.90 1 37 1 0
#> 157 15.10 1 47 0 0
#> 169 22.41 1 46 0 0
#> 188.1 16.16 1 46 0 1
#> 51 18.23 1 83 0 1
#> 169.1 22.41 1 46 0 0
#> 199 19.81 1 NA 0 1
#> 101 9.97 1 10 0 1
#> 164 23.60 1 76 0 1
#> 89 11.44 1 NA 0 0
#> 56 12.21 1 60 0 0
#> 195.1 11.76 1 NA 1 0
#> 180.1 14.82 1 37 0 0
#> 25.1 6.32 1 34 1 0
#> 52.1 10.42 1 52 0 1
#> 100 16.07 1 60 0 0
#> 8 18.43 1 32 0 0
#> 8.1 18.43 1 32 0 0
#> 136 21.83 1 43 0 1
#> 32.2 20.90 1 37 1 0
#> 60 13.15 1 38 1 0
#> 93.1 10.33 1 52 0 1
#> 170 19.54 1 43 0 1
#> 177 12.53 1 75 0 0
#> 8.2 18.43 1 32 0 0
#> 177.1 12.53 1 75 0 0
#> 61 10.12 1 36 0 1
#> 24 23.89 1 38 0 0
#> 197 21.60 1 69 1 0
#> 25.2 6.32 1 34 1 0
#> 88.1 18.37 1 47 0 0
#> 114 13.68 1 NA 0 0
#> 51.1 18.23 1 83 0 1
#> 134 17.81 1 47 1 0
#> 105 19.75 1 60 0 0
#> 108 18.29 1 39 0 1
#> 23 16.92 1 61 0 0
#> 134.1 17.81 1 47 1 0
#> 175 21.91 1 43 0 0
#> 51.2 18.23 1 83 0 1
#> 184 17.77 1 38 0 0
#> 32.3 20.90 1 37 1 0
#> 136.1 21.83 1 43 0 1
#> 6 15.64 1 39 0 0
#> 50 10.02 1 NA 1 0
#> 76 19.22 1 54 0 1
#> 168 23.72 1 70 0 0
#> 170.1 19.54 1 43 0 1
#> 39.1 15.59 1 37 0 1
#> 92.1 22.92 1 47 0 1
#> 13.1 14.34 1 54 0 1
#> 123.1 13.00 1 44 1 0
#> 179 18.63 1 42 0 0
#> 30 17.43 1 78 0 0
#> 88.2 18.37 1 47 0 0
#> 133 14.65 1 57 0 0
#> 180.2 14.82 1 37 0 0
#> 111 17.45 1 47 0 1
#> 192 16.44 1 31 1 0
#> 58 19.34 1 39 0 0
#> 149 8.37 1 33 1 0
#> 77 7.27 1 67 0 1
#> 170.2 19.54 1 43 0 1
#> 96 14.54 1 33 0 1
#> 128 20.35 1 35 0 1
#> 154.1 12.63 1 20 1 0
#> 88.3 18.37 1 47 0 0
#> 60.1 13.15 1 38 1 0
#> 179.1 18.63 1 42 0 0
#> 99 21.19 1 38 0 1
#> 168.1 23.72 1 70 0 0
#> 51.3 18.23 1 83 0 1
#> 55 19.34 1 69 0 1
#> 171.1 16.57 1 41 0 1
#> 136.2 21.83 1 43 0 1
#> 43 12.10 1 61 0 1
#> 14 12.89 1 21 0 0
#> 110 17.56 1 65 0 1
#> 49 12.19 1 48 1 0
#> 199.1 19.81 1 NA 0 1
#> 63 22.77 1 31 1 0
#> 190.1 20.81 1 42 1 0
#> 117 17.46 1 26 0 1
#> 167 15.55 1 56 1 0
#> 29 15.45 1 68 1 0
#> 140 12.68 1 59 1 0
#> 164.1 23.60 1 76 0 1
#> 103 24.00 0 56 1 0
#> 141 24.00 0 44 1 0
#> 131 24.00 0 66 0 0
#> 118 24.00 0 44 1 0
#> 20 24.00 0 46 1 0
#> 62 24.00 0 71 0 0
#> 178 24.00 0 52 1 0
#> 144 24.00 0 28 0 1
#> 186 24.00 0 45 1 0
#> 116 24.00 0 58 0 1
#> 65 24.00 0 57 1 0
#> 109 24.00 0 48 0 0
#> 191 24.00 0 60 0 1
#> 126 24.00 0 48 0 0
#> 165 24.00 0 47 0 0
#> 132 24.00 0 55 0 0
#> 38 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 67 24.00 0 25 0 0
#> 2 24.00 0 9 0 0
#> 142 24.00 0 53 0 0
#> 193 24.00 0 45 0 1
#> 173 24.00 0 19 0 1
#> 116.1 24.00 0 58 0 1
#> 138 24.00 0 44 1 0
#> 72 24.00 0 40 0 1
#> 176 24.00 0 43 0 1
#> 156 24.00 0 50 1 0
#> 173.1 24.00 0 19 0 1
#> 28 24.00 0 67 1 0
#> 9 24.00 0 31 1 0
#> 144.1 24.00 0 28 0 1
#> 1 24.00 0 23 1 0
#> 182 24.00 0 35 0 0
#> 126.1 24.00 0 48 0 0
#> 200 24.00 0 64 0 0
#> 174 24.00 0 49 1 0
#> 28.1 24.00 0 67 1 0
#> 74 24.00 0 43 0 1
#> 9.1 24.00 0 31 1 0
#> 118.1 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 22 24.00 0 52 1 0
#> 82 24.00 0 34 0 0
#> 74.1 24.00 0 43 0 1
#> 121 24.00 0 57 1 0
#> 178.1 24.00 0 52 1 0
#> 165.1 24.00 0 47 0 0
#> 67.1 24.00 0 25 0 0
#> 116.2 24.00 0 58 0 1
#> 143 24.00 0 51 0 0
#> 83 24.00 0 6 0 0
#> 173.2 24.00 0 19 0 1
#> 156.1 24.00 0 50 1 0
#> 196 24.00 0 19 0 0
#> 31 24.00 0 36 0 1
#> 19 24.00 0 57 0 1
#> 146 24.00 0 63 1 0
#> 185 24.00 0 44 1 0
#> 163 24.00 0 66 0 0
#> 186.1 24.00 0 45 1 0
#> 3 24.00 0 31 1 0
#> 193.1 24.00 0 45 0 1
#> 83.1 24.00 0 6 0 0
#> 65.1 24.00 0 57 1 0
#> 116.3 24.00 0 58 0 1
#> 173.3 24.00 0 19 0 1
#> 28.2 24.00 0 67 1 0
#> 19.1 24.00 0 57 0 1
#> 65.2 24.00 0 57 1 0
#> 67.2 24.00 0 25 0 0
#> 146.1 24.00 0 63 1 0
#> 147 24.00 0 76 1 0
#> 73 24.00 0 NA 0 1
#> 196.1 24.00 0 19 0 0
#> 71.1 24.00 0 51 0 0
#> 185.1 24.00 0 44 1 0
#> 104 24.00 0 50 1 0
#> 17 24.00 0 38 0 1
#> 148 24.00 0 61 1 0
#> 33 24.00 0 53 0 0
#> 156.2 24.00 0 50 1 0
#> 19.2 24.00 0 57 0 1
#> 67.3 24.00 0 25 0 0
#> 2.1 24.00 0 9 0 0
#> 182.1 24.00 0 35 0 0
#> 54 24.00 0 53 1 0
#> 98 24.00 0 34 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.401 NA NA NA
#> 2 age, Cure model 0.0129 NA NA NA
#> 3 grade_ii, Cure model -0.451 NA NA NA
#> 4 grade_iii, Cure model 0.441 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00341 NA NA NA
#> 2 grade_ii, Survival model 0.669 NA NA NA
#> 3 grade_iii, Survival model 0.286 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.40059 0.01288 -0.45125 0.44088
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 255.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.40058828 0.01288437 -0.45124768 0.44087545
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003409052 0.668869382 0.285609792
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.017507476 0.692747140 0.583888409 0.943157641 0.781930711 0.816637114
#> [7] 0.082420683 0.249010710 0.901305821 0.647727172 0.991930601 0.926461056
#> [13] 0.611384073 0.286903648 0.156785337 0.967903864 0.156785337 0.107089920
#> [19] 0.884516595 0.426233054 0.737480442 0.850590158 0.755342431 0.249010710
#> [25] 0.683773954 0.132706733 0.611384073 0.472864905 0.132706733 0.934820008
#> [31] 0.056797222 0.859089017 0.692747140 0.967903864 0.884516595 0.629457258
#> [37] 0.398458894 0.398458894 0.192524266 0.249010710 0.764338571 0.901305821
#> [43] 0.324610363 0.833574630 0.398458894 0.833574630 0.918059347 0.005608699
#> [49] 0.226135102 0.967903864 0.426233054 0.472864905 0.509857469 0.315096626
#> [55] 0.463330714 0.574591974 0.509857469 0.180263100 0.472864905 0.528251366
#> [61] 0.249010710 0.192524266 0.638584080 0.370501061 0.031082133 0.324610363
#> [67] 0.647727172 0.082420683 0.737480442 0.781930711 0.379856852 0.565323695
#> [73] 0.426233054 0.719440966 0.692747140 0.556090763 0.602242288 0.351976412
#> [79] 0.951443341 0.959675680 0.324610363 0.728471257 0.305635748 0.816637114
#> [85] 0.426233054 0.764338571 0.379856852 0.237619339 0.031082133 0.472864905
#> [91] 0.351976412 0.583888409 0.192524266 0.876063322 0.799257744 0.537549647
#> [97] 0.867603457 0.120411553 0.286903648 0.546837311 0.665796758 0.674818168
#> [103] 0.807975296 0.056797222 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 78 180 171 187 123 154 92 32 93 39 127 145 188
#> 23.88 14.82 16.57 9.92 13.00 12.63 22.92 20.90 10.33 15.59 3.53 10.07 16.16
#> 190 194 25 194.1 113 52 88 13 37 81 32.1 157 169
#> 20.81 22.40 6.32 22.40 22.86 10.42 18.37 14.34 12.52 14.06 20.90 15.10 22.41
#> 188.1 51 169.1 101 164 56 180.1 25.1 52.1 100 8 8.1 136
#> 16.16 18.23 22.41 9.97 23.60 12.21 14.82 6.32 10.42 16.07 18.43 18.43 21.83
#> 32.2 60 93.1 170 177 8.2 177.1 61 24 197 25.2 88.1 51.1
#> 20.90 13.15 10.33 19.54 12.53 18.43 12.53 10.12 23.89 21.60 6.32 18.37 18.23
#> 134 105 108 23 134.1 175 51.2 184 32.3 136.1 6 76 168
#> 17.81 19.75 18.29 16.92 17.81 21.91 18.23 17.77 20.90 21.83 15.64 19.22 23.72
#> 170.1 39.1 92.1 13.1 123.1 179 30 88.2 133 180.2 111 192 58
#> 19.54 15.59 22.92 14.34 13.00 18.63 17.43 18.37 14.65 14.82 17.45 16.44 19.34
#> 149 77 170.2 96 128 154.1 88.3 60.1 179.1 99 168.1 51.3 55
#> 8.37 7.27 19.54 14.54 20.35 12.63 18.37 13.15 18.63 21.19 23.72 18.23 19.34
#> 171.1 136.2 43 14 110 49 63 190.1 117 167 29 140 164.1
#> 16.57 21.83 12.10 12.89 17.56 12.19 22.77 20.81 17.46 15.55 15.45 12.68 23.60
#> 103 141 131 118 20 62 178 144 186 116 65 109 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 165 132 38 71 67 2 142 193 173 116.1 138 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 156 173.1 28 9 144.1 1 182 126.1 200 174 28.1 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.1 118.1 80 22 82 74.1 121 178.1 165.1 67.1 116.2 143 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173.2 156.1 196 31 19 146 185 163 186.1 3 193.1 83.1 65.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116.3 173.3 28.2 19.1 65.2 67.2 146.1 147 196.1 71.1 185.1 104 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 33 156.2 19.2 67.3 2.1 182.1 54 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[37]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01834695 0.70271222 0.54521781
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.34949681 0.01656772 1.24323394
#> grade_iii, Cure model
#> 1.04078816
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 37 12.52 1 57 1 0
#> 128 20.35 1 35 0 1
#> 25 6.32 1 34 1 0
#> 56 12.21 1 60 0 0
#> 150 20.33 1 48 0 0
#> 58 19.34 1 39 0 0
#> 158 20.14 1 74 1 0
#> 140 12.68 1 59 1 0
#> 61 10.12 1 36 0 1
#> 184 17.77 1 38 0 0
#> 154 12.63 1 20 1 0
#> 170 19.54 1 43 0 1
#> 183 9.24 1 67 1 0
#> 157 15.10 1 47 0 0
#> 39 15.59 1 37 0 1
#> 123 13.00 1 44 1 0
#> 60 13.15 1 38 1 0
#> 183.1 9.24 1 67 1 0
#> 52 10.42 1 52 0 1
#> 10 10.53 1 34 0 0
#> 15 22.68 1 48 0 0
#> 93 10.33 1 52 0 1
#> 42 12.43 1 49 0 1
#> 61.1 10.12 1 36 0 1
#> 136 21.83 1 43 0 1
#> 101 9.97 1 10 0 1
#> 32 20.90 1 37 1 0
#> 113 22.86 1 34 0 0
#> 149 8.37 1 33 1 0
#> 70 7.38 1 30 1 0
#> 52.1 10.42 1 52 0 1
#> 30 17.43 1 78 0 0
#> 134 17.81 1 47 1 0
#> 181 16.46 1 45 0 1
#> 139 21.49 1 63 1 0
#> 114 13.68 1 NA 0 0
#> 188 16.16 1 46 0 1
#> 18 15.21 1 49 1 0
#> 91 5.33 1 61 0 1
#> 61.2 10.12 1 36 0 1
#> 25.1 6.32 1 34 1 0
#> 76 19.22 1 54 0 1
#> 134.1 17.81 1 47 1 0
#> 79 16.23 1 54 1 0
#> 60.1 13.15 1 38 1 0
#> 25.2 6.32 1 34 1 0
#> 125 15.65 1 67 1 0
#> 52.2 10.42 1 52 0 1
#> 89 11.44 1 NA 0 0
#> 175 21.91 1 43 0 0
#> 184.1 17.77 1 38 0 0
#> 189 10.51 1 NA 1 0
#> 199 19.81 1 NA 0 1
#> 79.1 16.23 1 54 1 0
#> 125.1 15.65 1 67 1 0
#> 23 16.92 1 61 0 0
#> 195 11.76 1 NA 1 0
#> 171 16.57 1 41 0 1
#> 41 18.02 1 40 1 0
#> 158.1 20.14 1 74 1 0
#> 158.2 20.14 1 74 1 0
#> 49 12.19 1 48 1 0
#> 79.2 16.23 1 54 1 0
#> 169 22.41 1 46 0 0
#> 167 15.55 1 56 1 0
#> 108 18.29 1 39 0 1
#> 107 11.18 1 54 1 0
#> 127 3.53 1 62 0 1
#> 100 16.07 1 60 0 0
#> 179 18.63 1 42 0 0
#> 106 16.67 1 49 1 0
#> 197 21.60 1 69 1 0
#> 188.1 16.16 1 46 0 1
#> 50 10.02 1 NA 1 0
#> 43 12.10 1 61 0 1
#> 197.1 21.60 1 69 1 0
#> 97 19.14 1 65 0 1
#> 180 14.82 1 37 0 0
#> 199.1 19.81 1 NA 0 1
#> 167.1 15.55 1 56 1 0
#> 29 15.45 1 68 1 0
#> 42.1 12.43 1 49 0 1
#> 189.1 10.51 1 NA 1 0
#> 170.1 19.54 1 43 0 1
#> 189.2 10.51 1 NA 1 0
#> 49.1 12.19 1 48 1 0
#> 10.1 10.53 1 34 0 0
#> 129 23.41 1 53 1 0
#> 117 17.46 1 26 0 1
#> 10.2 10.53 1 34 0 0
#> 29.1 15.45 1 68 1 0
#> 114.1 13.68 1 NA 0 0
#> 4 17.64 1 NA 0 1
#> 130 16.47 1 53 0 1
#> 127.1 3.53 1 62 0 1
#> 56.1 12.21 1 60 0 0
#> 113.1 22.86 1 34 0 0
#> 187 9.92 1 39 1 0
#> 99 21.19 1 38 0 1
#> 97.1 19.14 1 65 0 1
#> 167.2 15.55 1 56 1 0
#> 164 23.60 1 76 0 1
#> 167.3 15.55 1 56 1 0
#> 96 14.54 1 33 0 1
#> 139.1 21.49 1 63 1 0
#> 26 15.77 1 49 0 1
#> 41.1 18.02 1 40 1 0
#> 30.1 17.43 1 78 0 0
#> 15.1 22.68 1 48 0 0
#> 157.1 15.10 1 47 0 0
#> 4.1 17.64 1 NA 0 1
#> 199.2 19.81 1 NA 0 1
#> 84 24.00 0 39 0 1
#> 165 24.00 0 47 0 0
#> 80 24.00 0 41 0 0
#> 162 24.00 0 51 0 0
#> 162.1 24.00 0 51 0 0
#> 162.2 24.00 0 51 0 0
#> 161 24.00 0 45 0 0
#> 143 24.00 0 51 0 0
#> 27 24.00 0 63 1 0
#> 74 24.00 0 43 0 1
#> 48 24.00 0 31 1 0
#> 112 24.00 0 61 0 0
#> 1 24.00 0 23 1 0
#> 54 24.00 0 53 1 0
#> 143.1 24.00 0 51 0 0
#> 3 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#> 116 24.00 0 58 0 1
#> 160 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 67 24.00 0 25 0 0
#> 152.1 24.00 0 36 0 1
#> 53 24.00 0 32 0 1
#> 147 24.00 0 76 1 0
#> 73 24.00 0 NA 0 1
#> 11 24.00 0 42 0 1
#> 115 24.00 0 NA 1 0
#> 160.1 24.00 0 31 1 0
#> 20 24.00 0 46 1 0
#> 176 24.00 0 43 0 1
#> 151 24.00 0 42 0 0
#> 67.1 24.00 0 25 0 0
#> 186 24.00 0 45 1 0
#> 119 24.00 0 17 0 0
#> 104 24.00 0 50 1 0
#> 20.1 24.00 0 46 1 0
#> 162.3 24.00 0 51 0 0
#> 104.1 24.00 0 50 1 0
#> 20.2 24.00 0 46 1 0
#> 135 24.00 0 58 1 0
#> 21 24.00 0 47 0 0
#> 200 24.00 0 64 0 0
#> 132 24.00 0 55 0 0
#> 84.1 24.00 0 39 0 1
#> 176.1 24.00 0 43 0 1
#> 64 24.00 0 43 0 0
#> 87 24.00 0 27 0 0
#> 200.1 24.00 0 64 0 0
#> 132.1 24.00 0 55 0 0
#> 131 24.00 0 66 0 0
#> 185 24.00 0 44 1 0
#> 73.1 24.00 0 NA 0 1
#> 44 24.00 0 56 0 0
#> 151.1 24.00 0 42 0 0
#> 73.2 24.00 0 NA 0 1
#> 185.1 24.00 0 44 1 0
#> 115.1 24.00 0 NA 1 0
#> 161.1 24.00 0 45 0 0
#> 138 24.00 0 44 1 0
#> 35 24.00 0 51 0 0
#> 161.2 24.00 0 45 0 0
#> 74.1 24.00 0 43 0 1
#> 121 24.00 0 57 1 0
#> 64.1 24.00 0 43 0 0
#> 116.1 24.00 0 58 0 1
#> 80.1 24.00 0 41 0 0
#> 72 24.00 0 40 0 1
#> 122 24.00 0 66 0 0
#> 47 24.00 0 38 0 1
#> 151.2 24.00 0 42 0 0
#> 74.2 24.00 0 43 0 1
#> 193 24.00 0 45 0 1
#> 84.2 24.00 0 39 0 1
#> 132.2 24.00 0 55 0 0
#> 165.1 24.00 0 47 0 0
#> 94 24.00 0 51 0 1
#> 135.1 24.00 0 58 1 0
#> 102 24.00 0 49 0 0
#> 165.2 24.00 0 47 0 0
#> 11.1 24.00 0 42 0 1
#> 44.1 24.00 0 56 0 0
#> 44.2 24.00 0 56 0 0
#> 35.1 24.00 0 51 0 0
#> 7 24.00 0 37 1 0
#> 115.2 24.00 0 NA 1 0
#> 95.1 24.00 0 68 0 1
#> 143.2 24.00 0 51 0 0
#> 109 24.00 0 48 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.35 NA NA NA
#> 2 age, Cure model 0.0166 NA NA NA
#> 3 grade_ii, Cure model 1.24 NA NA NA
#> 4 grade_iii, Cure model 1.04 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0183 NA NA NA
#> 2 grade_ii, Survival model 0.703 NA NA NA
#> 3 grade_iii, Survival model 0.545 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.34950 0.01657 1.24323 1.04079
#>
#> Degrees of Freedom: 180 Total (i.e. Null); 177 Residual
#> Null Deviance: 249.3
#> Residual Deviance: 234.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.34949681 0.01656772 1.24323394 1.04078816
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01834695 0.70271222 0.54521781
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.5766452936 0.0554325707 0.9155331856 0.6145180516 0.0612863976
#> [6] 0.1006302625 0.0674871921 0.5514766072 0.7891102150 0.1816962560
#> [11] 0.5641169502 0.0867751792 0.8589175093 0.4647319140 0.3729916854
#> [16] 0.5389271607 0.5141770574 0.8589175093 0.7338127761 0.6933549727
#> [21] 0.0058706704 0.7750336016 0.5892531937 0.7891102150 0.0191467142
#> [26] 0.8308304443 0.0496358055 0.0024260660 0.8871528445 0.9013613882
#> [31] 0.7338127761 0.2082819939 0.1649064603 0.2670524407 0.0331565410
#> [36] 0.3077608233 0.4527356183 0.9572376470 0.7891102150 0.9155331856
#> [41] 0.1080863868 0.1649064603 0.2773061499 0.5141770574 0.9155331856
#> [46] 0.3507236912 0.7338127761 0.0148895378 0.1816962560 0.2773061499
#> [51] 0.3507236912 0.2270575243 0.2468736185 0.1483663009 0.0674871921
#> [56] 0.0674871921 0.6404957645 0.2773061499 0.0112093583 0.3843400596
#> [61] 0.1398827941 0.6799679128 0.9714374494 0.3287790935 0.1314792294
#> [66] 0.2369286241 0.0236225505 0.3077608233 0.6666464936 0.0236225505
#> [71] 0.1157322656 0.4891334759 0.3843400596 0.4291707173 0.5892531937
#> [76] 0.0867751792 0.6404957645 0.6933549727 0.0010480442 0.1993034376
#> [81] 0.6933549727 0.4291707173 0.2568941372 0.9714374494 0.6145180516
#> [86] 0.0024260660 0.8448724875 0.0438234352 0.1157322656 0.3843400596
#> [91] 0.0001011921 0.3843400596 0.5016461238 0.0331565410 0.3396985811
#> [96] 0.1483663009 0.2082819939 0.0058706704 0.4647319140 0.0000000000
#> [101] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000
#>
#> $Time
#> 37 128 25 56 150 58 158 140 61 184 154 170 183
#> 12.52 20.35 6.32 12.21 20.33 19.34 20.14 12.68 10.12 17.77 12.63 19.54 9.24
#> 157 39 123 60 183.1 52 10 15 93 42 61.1 136 101
#> 15.10 15.59 13.00 13.15 9.24 10.42 10.53 22.68 10.33 12.43 10.12 21.83 9.97
#> 32 113 149 70 52.1 30 134 181 139 188 18 91 61.2
#> 20.90 22.86 8.37 7.38 10.42 17.43 17.81 16.46 21.49 16.16 15.21 5.33 10.12
#> 25.1 76 134.1 79 60.1 25.2 125 52.2 175 184.1 79.1 125.1 23
#> 6.32 19.22 17.81 16.23 13.15 6.32 15.65 10.42 21.91 17.77 16.23 15.65 16.92
#> 171 41 158.1 158.2 49 79.2 169 167 108 107 127 100 179
#> 16.57 18.02 20.14 20.14 12.19 16.23 22.41 15.55 18.29 11.18 3.53 16.07 18.63
#> 106 197 188.1 43 197.1 97 180 167.1 29 42.1 170.1 49.1 10.1
#> 16.67 21.60 16.16 12.10 21.60 19.14 14.82 15.55 15.45 12.43 19.54 12.19 10.53
#> 129 117 10.2 29.1 130 127.1 56.1 113.1 187 99 97.1 167.2 164
#> 23.41 17.46 10.53 15.45 16.47 3.53 12.21 22.86 9.92 21.19 19.14 15.55 23.60
#> 167.3 96 139.1 26 41.1 30.1 15.1 157.1 84 165 80 162 162.1
#> 15.55 14.54 21.49 15.77 18.02 17.43 22.68 15.10 24.00 24.00 24.00 24.00 24.00
#> 162.2 161 143 27 74 48 112 1 54 143.1 3 95 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160 152 67 152.1 53 147 11 160.1 20 176 151 67.1 186
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119 104 20.1 162.3 104.1 20.2 135 21 200 132 84.1 176.1 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 200.1 132.1 131 185 44 151.1 185.1 161.1 138 35 161.2 74.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 64.1 116.1 80.1 72 122 47 151.2 74.2 193 84.2 132.2 165.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 135.1 102 165.2 11.1 44.1 44.2 35.1 7 95.1 143.2 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[38]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0005172929 0.9007600168 0.3394109704
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.244016196 -0.002212477 0.688063023
#> grade_iii, Cure model
#> 0.961994424
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 56 12.21 1 60 0 0
#> 113 22.86 1 34 0 0
#> 130 16.47 1 53 0 1
#> 96 14.54 1 33 0 1
#> 30 17.43 1 78 0 0
#> 37 12.52 1 57 1 0
#> 145 10.07 1 65 1 0
#> 29 15.45 1 68 1 0
#> 70 7.38 1 30 1 0
#> 76 19.22 1 54 0 1
#> 24 23.89 1 38 0 0
#> 107 11.18 1 54 1 0
#> 50 10.02 1 NA 1 0
#> 166 19.98 1 48 0 0
#> 133 14.65 1 57 0 0
#> 18 15.21 1 49 1 0
#> 10 10.53 1 34 0 0
#> 107.1 11.18 1 54 1 0
#> 154 12.63 1 20 1 0
#> 70.1 7.38 1 30 1 0
#> 92 22.92 1 47 0 1
#> 189 10.51 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 13 14.34 1 54 0 1
#> 117 17.46 1 26 0 1
#> 127 3.53 1 62 0 1
#> 175 21.91 1 43 0 0
#> 99 21.19 1 38 0 1
#> 190 20.81 1 42 1 0
#> 190.1 20.81 1 42 1 0
#> 169 22.41 1 46 0 0
#> 194 22.40 1 38 0 1
#> 181 16.46 1 45 0 1
#> 184 17.77 1 38 0 0
#> 167 15.55 1 56 1 0
#> 25 6.32 1 34 1 0
#> 49 12.19 1 48 1 0
#> 192 16.44 1 31 1 0
#> 81 14.06 1 34 0 0
#> 181.1 16.46 1 45 0 1
#> 89 11.44 1 NA 0 0
#> 14 12.89 1 21 0 0
#> 57 14.46 1 45 0 1
#> 58 19.34 1 39 0 0
#> 179 18.63 1 42 0 0
#> 68 20.62 1 44 0 0
#> 101 9.97 1 10 0 1
#> 52 10.42 1 52 0 1
#> 59 10.16 1 NA 1 0
#> 130.1 16.47 1 53 0 1
#> 58.1 19.34 1 39 0 0
#> 37.1 12.52 1 57 1 0
#> 14.1 12.89 1 21 0 0
#> 41 18.02 1 40 1 0
#> 128 20.35 1 35 0 1
#> 149 8.37 1 33 1 0
#> 106 16.67 1 49 1 0
#> 50.1 10.02 1 NA 1 0
#> 195 11.76 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 51 18.23 1 83 0 1
#> 45 17.42 1 54 0 1
#> 133.1 14.65 1 57 0 0
#> 5 16.43 1 51 0 1
#> 29.1 15.45 1 68 1 0
#> 57.1 14.46 1 45 0 1
#> 197 21.60 1 69 1 0
#> 190.2 20.81 1 42 1 0
#> 114 13.68 1 NA 0 0
#> 192.1 16.44 1 31 1 0
#> 110 17.56 1 65 0 1
#> 149.1 8.37 1 33 1 0
#> 150 20.33 1 48 0 0
#> 175.1 21.91 1 43 0 0
#> 140 12.68 1 59 1 0
#> 89.1 11.44 1 NA 0 0
#> 49.1 12.19 1 48 1 0
#> 30.1 17.43 1 78 0 0
#> 139 21.49 1 63 1 0
#> 183 9.24 1 67 1 0
#> 15 22.68 1 48 0 0
#> 39 15.59 1 37 0 1
#> 170 19.54 1 43 0 1
#> 58.2 19.34 1 39 0 0
#> 99.1 21.19 1 38 0 1
#> 70.2 7.38 1 30 1 0
#> 60 13.15 1 38 1 0
#> 55 19.34 1 69 0 1
#> 175.2 21.91 1 43 0 0
#> 127.1 3.53 1 62 0 1
#> 149.2 8.37 1 33 1 0
#> 45.1 17.42 1 54 0 1
#> 90 20.94 1 50 0 1
#> 40 18.00 1 28 1 0
#> 145.1 10.07 1 65 1 0
#> 91 5.33 1 61 0 1
#> 13.1 14.34 1 54 0 1
#> 134 17.81 1 47 1 0
#> 188 16.16 1 46 0 1
#> 59.1 10.16 1 NA 1 0
#> 79 16.23 1 54 1 0
#> 25.1 6.32 1 34 1 0
#> 155 13.08 1 26 0 0
#> 199 19.81 1 NA 0 1
#> 41.1 18.02 1 40 1 0
#> 149.3 8.37 1 33 1 0
#> 181.2 16.46 1 45 0 1
#> 51.1 18.23 1 83 0 1
#> 155.1 13.08 1 26 0 0
#> 177.1 12.53 1 75 0 0
#> 180 14.82 1 37 0 0
#> 99.2 21.19 1 38 0 1
#> 74 24.00 0 43 0 1
#> 200 24.00 0 64 0 0
#> 53 24.00 0 32 0 1
#> 38 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 196 24.00 0 19 0 0
#> 137 24.00 0 45 1 0
#> 132 24.00 0 55 0 0
#> 120 24.00 0 68 0 1
#> 71 24.00 0 51 0 0
#> 143 24.00 0 51 0 0
#> 191 24.00 0 60 0 1
#> 160 24.00 0 31 1 0
#> 144 24.00 0 28 0 1
#> 53.1 24.00 0 32 0 1
#> 191.1 24.00 0 60 0 1
#> 138 24.00 0 44 1 0
#> 21 24.00 0 47 0 0
#> 132.1 24.00 0 55 0 0
#> 44 24.00 0 56 0 0
#> 46 24.00 0 71 0 0
#> 102 24.00 0 49 0 0
#> 12 24.00 0 63 0 0
#> 33 24.00 0 53 0 0
#> 46.1 24.00 0 71 0 0
#> 156 24.00 0 50 1 0
#> 38.1 24.00 0 31 1 0
#> 46.2 24.00 0 71 0 0
#> 67 24.00 0 25 0 0
#> 27 24.00 0 63 1 0
#> 119 24.00 0 17 0 0
#> 121 24.00 0 57 1 0
#> 28 24.00 0 67 1 0
#> 20 24.00 0 46 1 0
#> 200.1 24.00 0 64 0 0
#> 182 24.00 0 35 0 0
#> 165 24.00 0 47 0 0
#> 20.1 24.00 0 46 1 0
#> 152 24.00 0 36 0 1
#> 21.1 24.00 0 47 0 0
#> 172 24.00 0 41 0 0
#> 75 24.00 0 21 1 0
#> 172.1 24.00 0 41 0 0
#> 137.1 24.00 0 45 1 0
#> 95 24.00 0 68 0 1
#> 116 24.00 0 58 0 1
#> 109.1 24.00 0 48 0 0
#> 94 24.00 0 51 0 1
#> 163 24.00 0 66 0 0
#> 82 24.00 0 34 0 0
#> 172.2 24.00 0 41 0 0
#> 33.1 24.00 0 53 0 0
#> 48 24.00 0 31 1 0
#> 64 24.00 0 43 0 0
#> 38.2 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 94.1 24.00 0 51 0 1
#> 34 24.00 0 36 0 0
#> 11 24.00 0 42 0 1
#> 2 24.00 0 9 0 0
#> 94.2 24.00 0 51 0 1
#> 46.3 24.00 0 71 0 0
#> 131 24.00 0 66 0 0
#> 109.2 24.00 0 48 0 0
#> 28.1 24.00 0 67 1 0
#> 104 24.00 0 50 1 0
#> 152.1 24.00 0 36 0 1
#> 156.1 24.00 0 50 1 0
#> 147 24.00 0 76 1 0
#> 27.1 24.00 0 63 1 0
#> 151 24.00 0 42 0 0
#> 9 24.00 0 31 1 0
#> 2.1 24.00 0 9 0 0
#> 54 24.00 0 53 1 0
#> 115 24.00 0 NA 1 0
#> 75.1 24.00 0 21 1 0
#> 119.1 24.00 0 17 0 0
#> 186 24.00 0 45 1 0
#> 144.1 24.00 0 28 0 1
#> 141 24.00 0 44 1 0
#> 12.1 24.00 0 63 0 0
#> 46.4 24.00 0 71 0 0
#> 176 24.00 0 43 0 1
#> 103 24.00 0 56 1 0
#> 67.1 24.00 0 25 0 0
#> 161 24.00 0 45 0 0
#> 94.3 24.00 0 51 0 1
#> 28.2 24.00 0 67 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.244 NA NA NA
#> 2 age, Cure model -0.00221 NA NA NA
#> 3 grade_ii, Cure model 0.688 NA NA NA
#> 4 grade_iii, Cure model 0.962 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000517 NA NA NA
#> 2 grade_ii, Survival model 0.901 NA NA NA
#> 3 grade_iii, Survival model 0.339 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.244016 -0.002212 0.688063 0.961994
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 253.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.244016196 -0.002212477 0.688063023 0.961994424
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0005172929 0.9007600168 0.3394109704
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.85318540 0.05999449 0.58068131 0.72806434 0.53484644 0.83911643
#> [7] 0.90096786 0.68205629 0.95205098 0.41477303 0.01414042 0.87400860
#> [13] 0.34981095 0.71282597 0.69751643 0.88747095 0.87400860 0.81748255
#> [19] 0.95205098 0.03920832 0.52551784 0.75075653 0.51612751 0.98813729
#> [25] 0.14339603 0.22847615 0.28261985 0.28261985 0.10213671 0.12340982
#> [31] 0.59837920 0.49715070 0.67403008 0.97022208 0.86025092 0.62430454
#> [37] 0.76571014 0.59837920 0.79539779 0.73569328 0.37233001 0.42571070
#> [43] 0.31573160 0.91412507 0.89422875 0.58068131 0.37233001 0.83911643
#> [49] 0.79539779 0.45790491 0.32718826 0.92722800 0.57166250 0.82471177
#> [55] 0.43665444 0.55336631 0.71282597 0.64104618 0.68205629 0.73569328
#> [61] 0.19602307 0.28261985 0.62430454 0.50667088 0.92722800 0.33849495
#> [67] 0.14339603 0.81016033 0.86025092 0.53484644 0.21310066 0.92070864
#> [73] 0.08098291 0.66586867 0.36113597 0.37233001 0.22847615 0.95205098
#> [79] 0.77322510 0.37233001 0.14339603 0.98813729 0.92722800 0.55336631
#> [85] 0.26873653 0.47784968 0.90096786 0.98216214 0.75075653 0.48763407
#> [91] 0.65766933 0.64943187 0.97022208 0.78063822 0.45790491 0.92722800
#> [97] 0.59837920 0.43665444 0.78063822 0.82471177 0.70517041 0.22847615
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 56 113 130 96 30 37 145 29 70 76 24 107 166
#> 12.21 22.86 16.47 14.54 17.43 12.52 10.07 15.45 7.38 19.22 23.89 11.18 19.98
#> 133 18 10 107.1 154 70.1 92 111 13 117 127 175 99
#> 14.65 15.21 10.53 11.18 12.63 7.38 22.92 17.45 14.34 17.46 3.53 21.91 21.19
#> 190 190.1 169 194 181 184 167 25 49 192 81 181.1 14
#> 20.81 20.81 22.41 22.40 16.46 17.77 15.55 6.32 12.19 16.44 14.06 16.46 12.89
#> 57 58 179 68 101 52 130.1 58.1 37.1 14.1 41 128 149
#> 14.46 19.34 18.63 20.62 9.97 10.42 16.47 19.34 12.52 12.89 18.02 20.35 8.37
#> 106 177 51 45 133.1 5 29.1 57.1 197 190.2 192.1 110 149.1
#> 16.67 12.53 18.23 17.42 14.65 16.43 15.45 14.46 21.60 20.81 16.44 17.56 8.37
#> 150 175.1 140 49.1 30.1 139 183 15 39 170 58.2 99.1 70.2
#> 20.33 21.91 12.68 12.19 17.43 21.49 9.24 22.68 15.59 19.54 19.34 21.19 7.38
#> 60 55 175.2 127.1 149.2 45.1 90 40 145.1 91 13.1 134 188
#> 13.15 19.34 21.91 3.53 8.37 17.42 20.94 18.00 10.07 5.33 14.34 17.81 16.16
#> 79 25.1 155 41.1 149.3 181.2 51.1 155.1 177.1 180 99.2 74 200
#> 16.23 6.32 13.08 18.02 8.37 16.46 18.23 13.08 12.53 14.82 21.19 24.00 24.00
#> 53 38 109 196 137 132 120 71 143 191 160 144 53.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191.1 138 21 132.1 44 46 102 12 33 46.1 156 38.1 46.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 27 119 121 28 20 200.1 182 165 20.1 152 21.1 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 172.1 137.1 95 116 109.1 94 163 82 172.2 33.1 48 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38.2 19 94.1 34 11 2 94.2 46.3 131 109.2 28.1 104 152.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156.1 147 27.1 151 9 2.1 54 75.1 119.1 186 144.1 141 12.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46.4 176 103 67.1 161 94.3 28.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[39]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0005425628 0.6289739537 0.5547526113
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.51460454 0.01270828 -0.03405160
#> grade_iii, Cure model
#> 0.12614413
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 149 8.37 1 33 1 0
#> 133 14.65 1 57 0 0
#> 169 22.41 1 46 0 0
#> 85 16.44 1 36 0 0
#> 68 20.62 1 44 0 0
#> 181 16.46 1 45 0 1
#> 117 17.46 1 26 0 1
#> 139 21.49 1 63 1 0
#> 149.1 8.37 1 33 1 0
#> 16 8.71 1 71 0 1
#> 14 12.89 1 21 0 0
#> 153 21.33 1 55 1 0
#> 153.1 21.33 1 55 1 0
#> 129 23.41 1 53 1 0
#> 168 23.72 1 70 0 0
#> 170 19.54 1 43 0 1
#> 91 5.33 1 61 0 1
#> 89 11.44 1 NA 0 0
#> 61 10.12 1 36 0 1
#> 188 16.16 1 46 0 1
#> 168.1 23.72 1 70 0 0
#> 190 20.81 1 42 1 0
#> 49 12.19 1 48 1 0
#> 100 16.07 1 60 0 0
#> 90 20.94 1 50 0 1
#> 30 17.43 1 78 0 0
#> 169.1 22.41 1 46 0 0
#> 127 3.53 1 62 0 1
#> 25 6.32 1 34 1 0
#> 18 15.21 1 49 1 0
#> 58 19.34 1 39 0 0
#> 105 19.75 1 60 0 0
#> 69 23.23 1 25 0 1
#> 169.2 22.41 1 46 0 0
#> 117.1 17.46 1 26 0 1
#> 60 13.15 1 38 1 0
#> 124 9.73 1 NA 1 0
#> 68.1 20.62 1 44 0 0
#> 51 18.23 1 83 0 1
#> 39 15.59 1 37 0 1
#> 184 17.77 1 38 0 0
#> 124.1 9.73 1 NA 1 0
#> 40 18.00 1 28 1 0
#> 42 12.43 1 49 0 1
#> 55 19.34 1 69 0 1
#> 24 23.89 1 38 0 0
#> 68.2 20.62 1 44 0 0
#> 170.1 19.54 1 43 0 1
#> 155 13.08 1 26 0 0
#> 23 16.92 1 61 0 0
#> 97 19.14 1 65 0 1
#> 168.2 23.72 1 70 0 0
#> 164 23.60 1 76 0 1
#> 76 19.22 1 54 0 1
#> 114 13.68 1 NA 0 0
#> 37 12.52 1 57 1 0
#> 107 11.18 1 54 1 0
#> 63 22.77 1 31 1 0
#> 124.2 9.73 1 NA 1 0
#> 40.1 18.00 1 28 1 0
#> 157 15.10 1 47 0 0
#> 187 9.92 1 39 1 0
#> 180 14.82 1 37 0 0
#> 89.1 11.44 1 NA 0 0
#> 180.1 14.82 1 37 0 0
#> 140 12.68 1 59 1 0
#> 8 18.43 1 32 0 0
#> 189 10.51 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 113 22.86 1 34 0 0
#> 123 13.00 1 44 1 0
#> 89.2 11.44 1 NA 0 0
#> 85.1 16.44 1 36 0 0
#> 77 7.27 1 67 0 1
#> 56 12.21 1 60 0 0
#> 158 20.14 1 74 1 0
#> 97.1 19.14 1 65 0 1
#> 199 19.81 1 NA 0 1
#> 56.1 12.21 1 60 0 0
#> 105.1 19.75 1 60 0 0
#> 30.1 17.43 1 78 0 0
#> 93 10.33 1 52 0 1
#> 166 19.98 1 48 0 0
#> 134 17.81 1 47 1 0
#> 117.2 17.46 1 26 0 1
#> 187.1 9.92 1 39 1 0
#> 56.2 12.21 1 60 0 0
#> 107.1 11.18 1 54 1 0
#> 4 17.64 1 NA 0 1
#> 77.1 7.27 1 67 0 1
#> 16.1 8.71 1 71 0 1
#> 5 16.43 1 51 0 1
#> 124.3 9.73 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 130 16.47 1 53 0 1
#> 56.3 12.21 1 60 0 0
#> 42.1 12.43 1 49 0 1
#> 167.1 15.55 1 56 1 0
#> 164.1 23.60 1 76 0 1
#> 69.1 23.23 1 25 0 1
#> 91.1 5.33 1 61 0 1
#> 32 20.90 1 37 1 0
#> 4.1 17.64 1 NA 0 1
#> 16.2 8.71 1 71 0 1
#> 175 21.91 1 43 0 0
#> 167.2 15.55 1 56 1 0
#> 78 23.88 1 43 0 0
#> 29 15.45 1 68 1 0
#> 189.1 10.51 1 NA 1 0
#> 5.1 16.43 1 51 0 1
#> 130.1 16.47 1 53 0 1
#> 52 10.42 1 52 0 1
#> 12 24.00 0 63 0 0
#> 53 24.00 0 32 0 1
#> 152 24.00 0 36 0 1
#> 27 24.00 0 63 1 0
#> 132 24.00 0 55 0 0
#> 173 24.00 0 19 0 1
#> 173.1 24.00 0 19 0 1
#> 131 24.00 0 66 0 0
#> 185 24.00 0 44 1 0
#> 196 24.00 0 19 0 0
#> 148 24.00 0 61 1 0
#> 163 24.00 0 66 0 0
#> 173.2 24.00 0 19 0 1
#> 84 24.00 0 39 0 1
#> 186 24.00 0 45 1 0
#> 165 24.00 0 47 0 0
#> 11 24.00 0 42 0 1
#> 156 24.00 0 50 1 0
#> 121 24.00 0 57 1 0
#> 34 24.00 0 36 0 0
#> 146 24.00 0 63 1 0
#> 20 24.00 0 46 1 0
#> 176 24.00 0 43 0 1
#> 126 24.00 0 48 0 0
#> 47 24.00 0 38 0 1
#> 98 24.00 0 34 1 0
#> 53.1 24.00 0 32 0 1
#> 182 24.00 0 35 0 0
#> 74 24.00 0 43 0 1
#> 137 24.00 0 45 1 0
#> 62 24.00 0 71 0 0
#> 131.1 24.00 0 66 0 0
#> 132.1 24.00 0 55 0 0
#> 27.1 24.00 0 63 1 0
#> 80 24.00 0 41 0 0
#> 142 24.00 0 53 0 0
#> 64 24.00 0 43 0 0
#> 71 24.00 0 51 0 0
#> 132.2 24.00 0 55 0 0
#> 115 24.00 0 NA 1 0
#> 135 24.00 0 58 1 0
#> 191 24.00 0 60 0 1
#> 142.1 24.00 0 53 0 0
#> 104 24.00 0 50 1 0
#> 33 24.00 0 53 0 0
#> 95 24.00 0 68 0 1
#> 72 24.00 0 40 0 1
#> 193 24.00 0 45 0 1
#> 84.1 24.00 0 39 0 1
#> 82 24.00 0 34 0 0
#> 147 24.00 0 76 1 0
#> 160 24.00 0 31 1 0
#> 200 24.00 0 64 0 0
#> 72.1 24.00 0 40 0 1
#> 135.1 24.00 0 58 1 0
#> 152.1 24.00 0 36 0 1
#> 33.1 24.00 0 53 0 0
#> 98.1 24.00 0 34 1 0
#> 102 24.00 0 49 0 0
#> 173.3 24.00 0 19 0 1
#> 161 24.00 0 45 0 0
#> 185.1 24.00 0 44 1 0
#> 54 24.00 0 53 1 0
#> 33.2 24.00 0 53 0 0
#> 198 24.00 0 66 0 1
#> 118 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 141 24.00 0 44 1 0
#> 173.4 24.00 0 19 0 1
#> 116 24.00 0 58 0 1
#> 95.1 24.00 0 68 0 1
#> 121.1 24.00 0 57 1 0
#> 162 24.00 0 51 0 0
#> 165.1 24.00 0 47 0 0
#> 191.1 24.00 0 60 0 1
#> 19 24.00 0 57 0 1
#> 151 24.00 0 42 0 0
#> 152.2 24.00 0 36 0 1
#> 31 24.00 0 36 0 1
#> 151.1 24.00 0 42 0 0
#> 185.2 24.00 0 44 1 0
#> 115.1 24.00 0 NA 1 0
#> 144 24.00 0 28 0 1
#> 103 24.00 0 56 1 0
#> 148.1 24.00 0 61 1 0
#> 112 24.00 0 61 0 0
#> 95.2 24.00 0 68 0 1
#> 112.1 24.00 0 61 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.515 NA NA NA
#> 2 age, Cure model 0.0127 NA NA NA
#> 3 grade_ii, Cure model -0.0341 NA NA NA
#> 4 grade_iii, Cure model 0.126 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000543 NA NA NA
#> 2 grade_ii, Survival model 0.629 NA NA NA
#> 3 grade_iii, Survival model 0.555 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.51460 0.01271 -0.03405 0.12614
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 255.6
#> Residual Deviance: 254 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.51460454 0.01270828 -0.03405160 0.12614413
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0005425628 0.6289739537 0.5547526113
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.94474681 0.76446045 0.22762214 0.64138662 0.36215274 0.63274517
#> [7] 0.56258824 0.29272492 0.94474681 0.92355677 0.79606444 0.30534656
#> [13] 0.30534656 0.15575231 0.06567705 0.43642400 0.97953119 0.90182233
#> [19] 0.67543212 0.06567705 0.35124424 0.86462226 0.68384664 0.32852976
#> [25] 0.58885123 0.22762214 0.99318275 0.97261522 0.73268893 0.45684233
#> [31] 0.41531328 0.17211647 0.22762214 0.56258824 0.77242839 0.36215274
#> [37] 0.51603947 0.69226448 0.55338097 0.52566709 0.81938938 0.45684233
#> [43] 0.01419387 0.36215274 0.43642400 0.78032809 0.60651466 0.48698795
#> [49] 0.06567705 0.12199485 0.47696560 0.81167535 0.87218599 0.21405455
#> [55] 0.52566709 0.74064970 0.90915133 0.74861262 0.74861262 0.80390083
#> [61] 0.50629095 0.70061058 0.19972038 0.78822891 0.64138662 0.95874980
#> [67] 0.83454718 0.39396995 0.48698795 0.83454718 0.41531328 0.58885123
#> [73] 0.89445093 0.40463799 0.54417683 0.56258824 0.90915133 0.83454718
#> [79] 0.87218599 0.95874980 0.92355677 0.65856202 0.27964513 0.61541588
#> [85] 0.83454718 0.81938938 0.70061058 0.12199485 0.17211647 0.97953119
#> [91] 0.34004595 0.92355677 0.26612192 0.70061058 0.03939510 0.72465603
#> [97] 0.65856202 0.61541588 0.88703718 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 149 133 169 85 68 181 117 139 149.1 16 14 153 153.1
#> 8.37 14.65 22.41 16.44 20.62 16.46 17.46 21.49 8.37 8.71 12.89 21.33 21.33
#> 129 168 170 91 61 188 168.1 190 49 100 90 30 169.1
#> 23.41 23.72 19.54 5.33 10.12 16.16 23.72 20.81 12.19 16.07 20.94 17.43 22.41
#> 127 25 18 58 105 69 169.2 117.1 60 68.1 51 39 184
#> 3.53 6.32 15.21 19.34 19.75 23.23 22.41 17.46 13.15 20.62 18.23 15.59 17.77
#> 40 42 55 24 68.2 170.1 155 23 97 168.2 164 76 37
#> 18.00 12.43 19.34 23.89 20.62 19.54 13.08 16.92 19.14 23.72 23.60 19.22 12.52
#> 107 63 40.1 157 187 180 180.1 140 8 167 113 123 85.1
#> 11.18 22.77 18.00 15.10 9.92 14.82 14.82 12.68 18.43 15.55 22.86 13.00 16.44
#> 77 56 158 97.1 56.1 105.1 30.1 93 166 134 117.2 187.1 56.2
#> 7.27 12.21 20.14 19.14 12.21 19.75 17.43 10.33 19.98 17.81 17.46 9.92 12.21
#> 107.1 77.1 16.1 5 136 130 56.3 42.1 167.1 164.1 69.1 91.1 32
#> 11.18 7.27 8.71 16.43 21.83 16.47 12.21 12.43 15.55 23.60 23.23 5.33 20.90
#> 16.2 175 167.2 78 29 5.1 130.1 52 12 53 152 27 132
#> 8.71 21.91 15.55 23.88 15.45 16.43 16.47 10.42 24.00 24.00 24.00 24.00 24.00
#> 173 173.1 131 185 196 148 163 173.2 84 186 165 11 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 34 146 20 176 126 47 98 53.1 182 74 137 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.1 132.1 27.1 80 142 64 71 132.2 135 191 142.1 104 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 72 193 84.1 82 147 160 200 72.1 135.1 152.1 33.1 98.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 173.3 161 185.1 54 33.2 198 118 7 141 173.4 116 95.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121.1 162 165.1 191.1 19 151 152.2 31 151.1 185.2 144 103 148.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 95.2 112.1
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[40]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01814229 0.15818173 0.53892450
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.39441275 0.02441688 -0.08439108
#> grade_iii, Cure model
#> 1.16706153
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 61 10.12 1 36 0 1
#> 107 11.18 1 54 1 0
#> 128 20.35 1 35 0 1
#> 158 20.14 1 74 1 0
#> 177 12.53 1 75 0 0
#> 16 8.71 1 71 0 1
#> 57 14.46 1 45 0 1
#> 51 18.23 1 83 0 1
#> 61.1 10.12 1 36 0 1
#> 63 22.77 1 31 1 0
#> 23 16.92 1 61 0 0
#> 86 23.81 1 58 0 1
#> 180 14.82 1 37 0 0
#> 14 12.89 1 21 0 0
#> 197 21.60 1 69 1 0
#> 13 14.34 1 54 0 1
#> 123 13.00 1 44 1 0
#> 150 20.33 1 48 0 0
#> 107.1 11.18 1 54 1 0
#> 43 12.10 1 61 0 1
#> 52 10.42 1 52 0 1
#> 66 22.13 1 53 0 0
#> 58 19.34 1 39 0 0
#> 59 10.16 1 NA 1 0
#> 189 10.51 1 NA 1 0
#> 97 19.14 1 65 0 1
#> 180.1 14.82 1 37 0 0
#> 195 11.76 1 NA 1 0
#> 158.1 20.14 1 74 1 0
#> 170 19.54 1 43 0 1
#> 24 23.89 1 38 0 0
#> 69 23.23 1 25 0 1
#> 25 6.32 1 34 1 0
#> 105 19.75 1 60 0 0
#> 43.1 12.10 1 61 0 1
#> 30 17.43 1 78 0 0
#> 63.1 22.77 1 31 1 0
#> 57.1 14.46 1 45 0 1
#> 97.1 19.14 1 65 0 1
#> 127 3.53 1 62 0 1
#> 78 23.88 1 43 0 0
#> 130 16.47 1 53 0 1
#> 140 12.68 1 59 1 0
#> 66.1 22.13 1 53 0 0
#> 59.1 10.16 1 NA 1 0
#> 180.2 14.82 1 37 0 0
#> 114 13.68 1 NA 0 0
#> 26 15.77 1 49 0 1
#> 13.1 14.34 1 54 0 1
#> 157 15.10 1 47 0 0
#> 16.1 8.71 1 71 0 1
#> 90 20.94 1 50 0 1
#> 4 17.64 1 NA 0 1
#> 57.2 14.46 1 45 0 1
#> 13.2 14.34 1 54 0 1
#> 85 16.44 1 36 0 0
#> 76 19.22 1 54 0 1
#> 23.1 16.92 1 61 0 0
#> 134 17.81 1 47 1 0
#> 30.1 17.43 1 78 0 0
#> 150.1 20.33 1 48 0 0
#> 42 12.43 1 49 0 1
#> 150.2 20.33 1 48 0 0
#> 159 10.55 1 50 0 1
#> 14.1 12.89 1 21 0 0
#> 169 22.41 1 46 0 0
#> 136 21.83 1 43 0 1
#> 129 23.41 1 53 1 0
#> 111 17.45 1 47 0 1
#> 18 15.21 1 49 1 0
#> 50 10.02 1 NA 1 0
#> 195.1 11.76 1 NA 1 0
#> 124 9.73 1 NA 1 0
#> 159.1 10.55 1 50 0 1
#> 58.1 19.34 1 39 0 0
#> 188 16.16 1 46 0 1
#> 188.1 16.16 1 46 0 1
#> 139 21.49 1 63 1 0
#> 59.2 10.16 1 NA 1 0
#> 130.1 16.47 1 53 0 1
#> 123.1 13.00 1 44 1 0
#> 15 22.68 1 48 0 0
#> 153 21.33 1 55 1 0
#> 90.1 20.94 1 50 0 1
#> 145 10.07 1 65 1 0
#> 129.1 23.41 1 53 1 0
#> 16.2 8.71 1 71 0 1
#> 36 21.19 1 48 0 1
#> 69.1 23.23 1 25 0 1
#> 77 7.27 1 67 0 1
#> 108 18.29 1 39 0 1
#> 187 9.92 1 39 1 0
#> 23.2 16.92 1 61 0 0
#> 85.1 16.44 1 36 0 0
#> 175 21.91 1 43 0 0
#> 36.1 21.19 1 48 0 1
#> 124.1 9.73 1 NA 1 0
#> 195.2 11.76 1 NA 1 0
#> 149 8.37 1 33 1 0
#> 127.1 3.53 1 62 0 1
#> 159.2 10.55 1 50 0 1
#> 150.3 20.33 1 48 0 0
#> 187.1 9.92 1 39 1 0
#> 79 16.23 1 54 1 0
#> 29 15.45 1 68 1 0
#> 43.2 12.10 1 61 0 1
#> 170.1 19.54 1 43 0 1
#> 177.1 12.53 1 75 0 0
#> 16.3 8.71 1 71 0 1
#> 183 9.24 1 67 1 0
#> 158.2 20.14 1 74 1 0
#> 79.1 16.23 1 54 1 0
#> 28 24.00 0 67 1 0
#> 12 24.00 0 63 0 0
#> 165 24.00 0 47 0 0
#> 178 24.00 0 52 1 0
#> 17 24.00 0 38 0 1
#> 178.1 24.00 0 52 1 0
#> 67 24.00 0 25 0 0
#> 33 24.00 0 53 0 0
#> 28.1 24.00 0 67 1 0
#> 160 24.00 0 31 1 0
#> 48 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 163 24.00 0 66 0 0
#> 19 24.00 0 57 0 1
#> 33.1 24.00 0 53 0 0
#> 186 24.00 0 45 1 0
#> 47 24.00 0 38 0 1
#> 151 24.00 0 42 0 0
#> 11 24.00 0 42 0 1
#> 162 24.00 0 51 0 0
#> 178.2 24.00 0 52 1 0
#> 148 24.00 0 61 1 0
#> 94 24.00 0 51 0 1
#> 162.1 24.00 0 51 0 0
#> 172 24.00 0 41 0 0
#> 126 24.00 0 48 0 0
#> 141 24.00 0 44 1 0
#> 28.2 24.00 0 67 1 0
#> 75 24.00 0 21 1 0
#> 80 24.00 0 41 0 0
#> 12.1 24.00 0 63 0 0
#> 104 24.00 0 50 1 0
#> 104.1 24.00 0 50 1 0
#> 94.1 24.00 0 51 0 1
#> 172.1 24.00 0 41 0 0
#> 144 24.00 0 28 0 1
#> 116 24.00 0 58 0 1
#> 112 24.00 0 61 0 0
#> 135 24.00 0 58 1 0
#> 162.2 24.00 0 51 0 0
#> 174 24.00 0 49 1 0
#> 80.1 24.00 0 41 0 0
#> 185 24.00 0 44 1 0
#> 48.1 24.00 0 31 1 0
#> 132 24.00 0 55 0 0
#> 146 24.00 0 63 1 0
#> 120 24.00 0 68 0 1
#> 62 24.00 0 71 0 0
#> 185.1 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 165.1 24.00 0 47 0 0
#> 186.1 24.00 0 45 1 0
#> 161 24.00 0 45 0 0
#> 174.1 24.00 0 49 1 0
#> 132.1 24.00 0 55 0 0
#> 103 24.00 0 56 1 0
#> 54 24.00 0 53 1 0
#> 102 24.00 0 49 0 0
#> 146.1 24.00 0 63 1 0
#> 28.3 24.00 0 67 1 0
#> 38 24.00 0 31 1 0
#> 2 24.00 0 9 0 0
#> 115 24.00 0 NA 1 0
#> 38.1 24.00 0 31 1 0
#> 196 24.00 0 19 0 0
#> 65 24.00 0 57 1 0
#> 144.1 24.00 0 28 0 1
#> 35 24.00 0 51 0 0
#> 64 24.00 0 43 0 0
#> 11.1 24.00 0 42 0 1
#> 160.1 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 152 24.00 0 36 0 1
#> 21 24.00 0 47 0 0
#> 21.1 24.00 0 47 0 0
#> 62.1 24.00 0 71 0 0
#> 121 24.00 0 57 1 0
#> 87 24.00 0 27 0 0
#> 83 24.00 0 6 0 0
#> 186.2 24.00 0 45 1 0
#> 142 24.00 0 53 0 0
#> 17.1 24.00 0 38 0 1
#> 162.3 24.00 0 51 0 0
#> 74 24.00 0 43 0 1
#> 120.1 24.00 0 68 0 1
#> 132.2 24.00 0 55 0 0
#> 112.1 24.00 0 61 0 0
#> 17.2 24.00 0 38 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.39 NA NA NA
#> 2 age, Cure model 0.0244 NA NA NA
#> 3 grade_ii, Cure model -0.0844 NA NA NA
#> 4 grade_iii, Cure model 1.17 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0181 NA NA NA
#> 2 grade_ii, Survival model 0.158 NA NA NA
#> 3 grade_iii, Survival model 0.539 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.39441 0.02442 -0.08439 1.16706
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.8
#> Residual Deviance: 238.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.39441275 0.02441688 -0.08439108 1.16706153
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01814229 0.15818173 0.53892450
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.9553005 0.9354581 0.6397311 0.6815983 0.9142029 0.9742154 0.8716655
#> [8] 0.7624646 0.9553005 0.4345831 0.7894986 0.3097522 0.8590723 0.9028812
#> [15] 0.5643789 0.8837559 0.8952840 0.6487504 0.9354581 0.9251425 0.9520559
#> [22] 0.5058229 0.7245431 0.7444968 0.8590723 0.6815983 0.7108584 0.1475749
#> [29] 0.3943882 0.9915836 0.7035980 0.9251425 0.7791016 0.4345831 0.8716655
#> [36] 0.7444968 0.9944373 0.2437662 0.8044468 0.9104489 0.5058229 0.8590723
#> [43] 0.8417204 0.8837559 0.8547936 0.9742154 0.6212414 0.8716655 0.8837559
#> [50] 0.8140286 0.7379668 0.7894986 0.7680972 0.7791016 0.6487504 0.9215216
#> [57] 0.6487504 0.9422420 0.9028812 0.4889139 0.5506360 0.3457994 0.7736585
#> [64] 0.8504859 0.9422420 0.7245431 0.8327608 0.8327608 0.5771586 0.8044468
#> [71] 0.8952840 0.4712067 0.5892240 0.6212414 0.9616794 0.3457994 0.9742154
#> [78] 0.6007744 0.3943882 0.9887203 0.7565375 0.9648446 0.7894986 0.8140286
#> [85] 0.5358843 0.6007744 0.9858167 0.9944373 0.9422420 0.6487504 0.9648446
#> [92] 0.8235076 0.8461374 0.9251425 0.7108584 0.9142029 0.9742154 0.9711081
#> [99] 0.6815983 0.8235076 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 61 107 128 158 177 16 57 51 61.1 63 23 86 180
#> 10.12 11.18 20.35 20.14 12.53 8.71 14.46 18.23 10.12 22.77 16.92 23.81 14.82
#> 14 197 13 123 150 107.1 43 52 66 58 97 180.1 158.1
#> 12.89 21.60 14.34 13.00 20.33 11.18 12.10 10.42 22.13 19.34 19.14 14.82 20.14
#> 170 24 69 25 105 43.1 30 63.1 57.1 97.1 127 78 130
#> 19.54 23.89 23.23 6.32 19.75 12.10 17.43 22.77 14.46 19.14 3.53 23.88 16.47
#> 140 66.1 180.2 26 13.1 157 16.1 90 57.2 13.2 85 76 23.1
#> 12.68 22.13 14.82 15.77 14.34 15.10 8.71 20.94 14.46 14.34 16.44 19.22 16.92
#> 134 30.1 150.1 42 150.2 159 14.1 169 136 129 111 18 159.1
#> 17.81 17.43 20.33 12.43 20.33 10.55 12.89 22.41 21.83 23.41 17.45 15.21 10.55
#> 58.1 188 188.1 139 130.1 123.1 15 153 90.1 145 129.1 16.2 36
#> 19.34 16.16 16.16 21.49 16.47 13.00 22.68 21.33 20.94 10.07 23.41 8.71 21.19
#> 69.1 77 108 187 23.2 85.1 175 36.1 149 127.1 159.2 150.3 187.1
#> 23.23 7.27 18.29 9.92 16.92 16.44 21.91 21.19 8.37 3.53 10.55 20.33 9.92
#> 79 29 43.2 170.1 177.1 16.3 183 158.2 79.1 28 12 165 178
#> 16.23 15.45 12.10 19.54 12.53 8.71 9.24 20.14 16.23 24.00 24.00 24.00 24.00
#> 17 178.1 67 33 28.1 160 48 7 163 19 33.1 186 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151 11 162 178.2 148 94 162.1 172 126 141 28.2 75 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12.1 104 104.1 94.1 172.1 144 116 112 135 162.2 174 80.1 185
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48.1 132 146 120 62 185.1 165.1 186.1 161 174.1 132.1 103 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 146.1 28.3 38 2 38.1 196 65 144.1 35 64 11.1 160.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 152 21 21.1 62.1 121 87 83 186.2 142 17.1 162.3 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120.1 132.2 112.1 17.2
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[41]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0102253 1.0382929 0.8807088
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.85259991 0.01416735 0.36251860
#> grade_iii, Cure model
#> 0.83577472
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 154 12.63 1 20 1 0
#> 86 23.81 1 58 0 1
#> 117 17.46 1 26 0 1
#> 179 18.63 1 42 0 0
#> 127 3.53 1 62 0 1
#> 166 19.98 1 48 0 0
#> 197 21.60 1 69 1 0
#> 188 16.16 1 46 0 1
#> 39 15.59 1 37 0 1
#> 91 5.33 1 61 0 1
#> 108 18.29 1 39 0 1
#> 23 16.92 1 61 0 0
#> 85 16.44 1 36 0 0
#> 111 17.45 1 47 0 1
#> 88 18.37 1 47 0 0
#> 66 22.13 1 53 0 0
#> 58 19.34 1 39 0 0
#> 90 20.94 1 50 0 1
#> 100 16.07 1 60 0 0
#> 51 18.23 1 83 0 1
#> 76 19.22 1 54 0 1
#> 55 19.34 1 69 0 1
#> 59 10.16 1 NA 1 0
#> 86.1 23.81 1 58 0 1
#> 125 15.65 1 67 1 0
#> 183 9.24 1 67 1 0
#> 26 15.77 1 49 0 1
#> 113 22.86 1 34 0 0
#> 40 18.00 1 28 1 0
#> 117.1 17.46 1 26 0 1
#> 113.1 22.86 1 34 0 0
#> 134 17.81 1 47 1 0
#> 175 21.91 1 43 0 0
#> 192 16.44 1 31 1 0
#> 88.1 18.37 1 47 0 0
#> 127.1 3.53 1 62 0 1
#> 199 19.81 1 NA 0 1
#> 108.1 18.29 1 39 0 1
#> 181 16.46 1 45 0 1
#> 117.2 17.46 1 26 0 1
#> 154.1 12.63 1 20 1 0
#> 70 7.38 1 30 1 0
#> 15 22.68 1 48 0 0
#> 139 21.49 1 63 1 0
#> 36 21.19 1 48 0 1
#> 155 13.08 1 26 0 0
#> 18 15.21 1 49 1 0
#> 25 6.32 1 34 1 0
#> 123 13.00 1 44 1 0
#> 168 23.72 1 70 0 0
#> 134.1 17.81 1 47 1 0
#> 41 18.02 1 40 1 0
#> 106 16.67 1 49 1 0
#> 88.2 18.37 1 47 0 0
#> 26.1 15.77 1 49 0 1
#> 140 12.68 1 59 1 0
#> 108.2 18.29 1 39 0 1
#> 51.1 18.23 1 83 0 1
#> 56 12.21 1 60 0 0
#> 40.1 18.00 1 28 1 0
#> 184 17.77 1 38 0 0
#> 129 23.41 1 53 1 0
#> 124 9.73 1 NA 1 0
#> 158 20.14 1 74 1 0
#> 183.1 9.24 1 67 1 0
#> 183.2 9.24 1 67 1 0
#> 183.3 9.24 1 67 1 0
#> 127.2 3.53 1 62 0 1
#> 66.1 22.13 1 53 0 0
#> 97 19.14 1 65 0 1
#> 113.2 22.86 1 34 0 0
#> 89 11.44 1 NA 0 0
#> 153 21.33 1 55 1 0
#> 149 8.37 1 33 1 0
#> 24 23.89 1 38 0 0
#> 199.1 19.81 1 NA 0 1
#> 16 8.71 1 71 0 1
#> 154.2 12.63 1 20 1 0
#> 45 17.42 1 54 0 1
#> 190 20.81 1 42 1 0
#> 158.1 20.14 1 74 1 0
#> 195 11.76 1 NA 1 0
#> 61 10.12 1 36 0 1
#> 32 20.90 1 37 1 0
#> 66.2 22.13 1 53 0 0
#> 86.2 23.81 1 58 0 1
#> 190.1 20.81 1 42 1 0
#> 150 20.33 1 48 0 0
#> 51.2 18.23 1 83 0 1
#> 192.1 16.44 1 31 1 0
#> 78 23.88 1 43 0 0
#> 60 13.15 1 38 1 0
#> 37 12.52 1 57 1 0
#> 140.1 12.68 1 59 1 0
#> 110 17.56 1 65 0 1
#> 18.1 15.21 1 49 1 0
#> 59.1 10.16 1 NA 1 0
#> 127.3 3.53 1 62 0 1
#> 90.1 20.94 1 50 0 1
#> 15.1 22.68 1 48 0 0
#> 91.1 5.33 1 61 0 1
#> 171 16.57 1 41 0 1
#> 197.1 21.60 1 69 1 0
#> 100.1 16.07 1 60 0 0
#> 40.2 18.00 1 28 1 0
#> 188.1 16.16 1 46 0 1
#> 169 22.41 1 46 0 0
#> 93 10.33 1 52 0 1
#> 59.2 10.16 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 40.3 18.00 1 28 1 0
#> 66.3 22.13 1 53 0 0
#> 200 24.00 0 64 0 0
#> 185 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 3 24.00 0 31 1 0
#> 65 24.00 0 57 1 0
#> 137 24.00 0 45 1 0
#> 31 24.00 0 36 0 1
#> 75 24.00 0 21 1 0
#> 116 24.00 0 58 0 1
#> 87 24.00 0 27 0 0
#> 112 24.00 0 61 0 0
#> 33 24.00 0 53 0 0
#> 74 24.00 0 43 0 1
#> 138 24.00 0 44 1 0
#> 48 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 112.1 24.00 0 61 0 0
#> 87.1 24.00 0 27 0 0
#> 11 24.00 0 42 0 1
#> 80 24.00 0 41 0 0
#> 80.1 24.00 0 41 0 0
#> 20 24.00 0 46 1 0
#> 162 24.00 0 51 0 0
#> 115 24.00 0 NA 1 0
#> 131 24.00 0 66 0 0
#> 48.1 24.00 0 31 1 0
#> 131.1 24.00 0 66 0 0
#> 28 24.00 0 67 1 0
#> 173 24.00 0 19 0 1
#> 48.2 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 75.1 24.00 0 21 1 0
#> 198 24.00 0 66 0 1
#> 19 24.00 0 57 0 1
#> 82 24.00 0 34 0 0
#> 144 24.00 0 28 0 1
#> 151 24.00 0 42 0 0
#> 19.1 24.00 0 57 0 1
#> 104 24.00 0 50 1 0
#> 103 24.00 0 56 1 0
#> 144.1 24.00 0 28 0 1
#> 80.2 24.00 0 41 0 0
#> 141 24.00 0 44 1 0
#> 38 24.00 0 31 1 0
#> 22 24.00 0 52 1 0
#> 138.1 24.00 0 44 1 0
#> 20.1 24.00 0 46 1 0
#> 174 24.00 0 49 1 0
#> 9 24.00 0 31 1 0
#> 143 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 137.1 24.00 0 45 1 0
#> 172 24.00 0 41 0 0
#> 146 24.00 0 63 1 0
#> 17 24.00 0 38 0 1
#> 87.2 24.00 0 27 0 0
#> 163 24.00 0 66 0 0
#> 19.2 24.00 0 57 0 1
#> 142 24.00 0 53 0 0
#> 160 24.00 0 31 1 0
#> 84 24.00 0 39 0 1
#> 75.2 24.00 0 21 1 0
#> 73 24.00 0 NA 0 1
#> 182 24.00 0 35 0 0
#> 121 24.00 0 57 1 0
#> 191 24.00 0 60 0 1
#> 1.1 24.00 0 23 1 0
#> 53 24.00 0 32 0 1
#> 71 24.00 0 51 0 0
#> 62 24.00 0 71 0 0
#> 95 24.00 0 68 0 1
#> 165 24.00 0 47 0 0
#> 112.2 24.00 0 61 0 0
#> 73.1 24.00 0 NA 0 1
#> 172.1 24.00 0 41 0 0
#> 64 24.00 0 43 0 0
#> 138.2 24.00 0 44 1 0
#> 28.1 24.00 0 67 1 0
#> 120 24.00 0 68 0 1
#> 84.1 24.00 0 39 0 1
#> 156 24.00 0 50 1 0
#> 33.1 24.00 0 53 0 0
#> 172.2 24.00 0 41 0 0
#> 122 24.00 0 66 0 0
#> 142.1 24.00 0 53 0 0
#> 152 24.00 0 36 0 1
#> 46 24.00 0 71 0 0
#> 3.1 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.853 NA NA NA
#> 2 age, Cure model 0.0142 NA NA NA
#> 3 grade_ii, Cure model 0.363 NA NA NA
#> 4 grade_iii, Cure model 0.836 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0102 NA NA NA
#> 2 grade_ii, Survival model 1.04 NA NA NA
#> 3 grade_iii, Survival model 0.881 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.85260 0.01417 0.36252 0.83577
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.1
#> Residual Deviance: 253 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.85259991 0.01416735 0.36251860 0.83577472
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0102253 1.0382929 0.8807088
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.844948620 0.034496959 0.608939231 0.418694092 0.971575487 0.364904573
#> [7] 0.212177439 0.722136808 0.780509585 0.957138690 0.461989194 0.653198541
#> [13] 0.697051789 0.635446502 0.429491594 0.147967660 0.375753946 0.276634532
#> [19] 0.738762048 0.493131782 0.397223703 0.375753946 0.034496959 0.772188547
#> [25] 0.898169118 0.755560649 0.082336143 0.534599212 0.608939231 0.082336143
#> [31] 0.571808969 0.197935609 0.697051789 0.429491594 0.971575487 0.461989194
#> [37] 0.688397988 0.608939231 0.844948620 0.942526559 0.112640668 0.238369950
#> [43] 0.264204398 0.813040176 0.788773129 0.949860581 0.821125600 0.060615933
#> [49] 0.571808969 0.524211201 0.662106810 0.429491594 0.755560649 0.829147746
#> [55] 0.461989194 0.493131782 0.875327586 0.534599212 0.590270827 0.071998661
#> [61] 0.343768496 0.898169118 0.898169118 0.898169118 0.971575487 0.147967660
#> [67] 0.407992950 0.082336143 0.251489187 0.935130482 0.003705203 0.927674523
#> [73] 0.844948620 0.644346298 0.311522463 0.343768496 0.890593392 0.300019964
#> [79] 0.147967660 0.034496959 0.311522463 0.332810432 0.493131782 0.697051789
#> [85] 0.016193266 0.804973481 0.867711415 0.829147746 0.599622550 0.788773129
#> [91] 0.971575487 0.276634532 0.112640668 0.957138690 0.670930638 0.212177439
#> [97] 0.738762048 0.534599212 0.722136808 0.135563611 0.882974267 0.679686937
#> [103] 0.534599212 0.147967660 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 154 86 117 179 127 166 197 188 39 91 108 23 85
#> 12.63 23.81 17.46 18.63 3.53 19.98 21.60 16.16 15.59 5.33 18.29 16.92 16.44
#> 111 88 66 58 90 100 51 76 55 86.1 125 183 26
#> 17.45 18.37 22.13 19.34 20.94 16.07 18.23 19.22 19.34 23.81 15.65 9.24 15.77
#> 113 40 117.1 113.1 134 175 192 88.1 127.1 108.1 181 117.2 154.1
#> 22.86 18.00 17.46 22.86 17.81 21.91 16.44 18.37 3.53 18.29 16.46 17.46 12.63
#> 70 15 139 36 155 18 25 123 168 134.1 41 106 88.2
#> 7.38 22.68 21.49 21.19 13.08 15.21 6.32 13.00 23.72 17.81 18.02 16.67 18.37
#> 26.1 140 108.2 51.1 56 40.1 184 129 158 183.1 183.2 183.3 127.2
#> 15.77 12.68 18.29 18.23 12.21 18.00 17.77 23.41 20.14 9.24 9.24 9.24 3.53
#> 66.1 97 113.2 153 149 24 16 154.2 45 190 158.1 61 32
#> 22.13 19.14 22.86 21.33 8.37 23.89 8.71 12.63 17.42 20.81 20.14 10.12 20.90
#> 66.2 86.2 190.1 150 51.2 192.1 78 60 37 140.1 110 18.1 127.3
#> 22.13 23.81 20.81 20.33 18.23 16.44 23.88 13.15 12.52 12.68 17.56 15.21 3.53
#> 90.1 15.1 91.1 171 197.1 100.1 40.2 188.1 169 93 130 40.3 66.3
#> 20.94 22.68 5.33 16.57 21.60 16.07 18.00 16.16 22.41 10.33 16.47 18.00 22.13
#> 200 185 27 3 65 137 31 75 116 87 112 33 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 48 109 112.1 87.1 11 80 80.1 20 162 131 48.1 131.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 173 48.2 1 75.1 198 19 82 144 151 19.1 104 103
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144.1 80.2 141 38 22 138.1 20.1 174 9 143 44 137.1 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 17 87.2 163 19.2 142 160 84 75.2 182 121 191 1.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 71 62 95 165 112.2 172.1 64 138.2 28.1 120 84.1 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33.1 172.2 122 142.1 152 46 3.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[42]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.009785648 0.829134565 0.619354538
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.51888592 0.01221137 -0.28762008
#> grade_iii, Cure model
#> 0.83972562
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 187 9.92 1 39 1 0
#> 57 14.46 1 45 0 1
#> 157 15.10 1 47 0 0
#> 60 13.15 1 38 1 0
#> 89 11.44 1 NA 0 0
#> 25 6.32 1 34 1 0
#> 77 7.27 1 67 0 1
#> 187.1 9.92 1 39 1 0
#> 79 16.23 1 54 1 0
#> 45 17.42 1 54 0 1
#> 169 22.41 1 46 0 0
#> 55 19.34 1 69 0 1
#> 10 10.53 1 34 0 0
#> 93 10.33 1 52 0 1
#> 91 5.33 1 61 0 1
#> 29 15.45 1 68 1 0
#> 49 12.19 1 48 1 0
#> 153 21.33 1 55 1 0
#> 130 16.47 1 53 0 1
#> 145 10.07 1 65 1 0
#> 166 19.98 1 48 0 0
#> 45.1 17.42 1 54 0 1
#> 134 17.81 1 47 1 0
#> 90 20.94 1 50 0 1
#> 197 21.60 1 69 1 0
#> 68 20.62 1 44 0 0
#> 8 18.43 1 32 0 0
#> 199 19.81 1 NA 0 1
#> 77.1 7.27 1 67 0 1
#> 91.1 5.33 1 61 0 1
#> 130.1 16.47 1 53 0 1
#> 108 18.29 1 39 0 1
#> 23 16.92 1 61 0 0
#> 124 9.73 1 NA 1 0
#> 180 14.82 1 37 0 0
#> 92 22.92 1 47 0 1
#> 70 7.38 1 30 1 0
#> 58 19.34 1 39 0 0
#> 37 12.52 1 57 1 0
#> 107 11.18 1 54 1 0
#> 179 18.63 1 42 0 0
#> 136 21.83 1 43 0 1
#> 76 19.22 1 54 0 1
#> 166.1 19.98 1 48 0 0
#> 5 16.43 1 51 0 1
#> 190 20.81 1 42 1 0
#> 23.1 16.92 1 61 0 0
#> 55.1 19.34 1 69 0 1
#> 101 9.97 1 10 0 1
#> 179.1 18.63 1 42 0 0
#> 16 8.71 1 71 0 1
#> 184 17.77 1 38 0 0
#> 179.2 18.63 1 42 0 0
#> 30 17.43 1 78 0 0
#> 180.1 14.82 1 37 0 0
#> 113 22.86 1 34 0 0
#> 55.2 19.34 1 69 0 1
#> 130.2 16.47 1 53 0 1
#> 16.1 8.71 1 71 0 1
#> 55.3 19.34 1 69 0 1
#> 96 14.54 1 33 0 1
#> 154 12.63 1 20 1 0
#> 77.2 7.27 1 67 0 1
#> 15 22.68 1 48 0 0
#> 170 19.54 1 43 0 1
#> 169.1 22.41 1 46 0 0
#> 6 15.64 1 39 0 0
#> 127 3.53 1 62 0 1
#> 150 20.33 1 48 0 0
#> 25.1 6.32 1 34 1 0
#> 14 12.89 1 21 0 0
#> 168 23.72 1 70 0 0
#> 157.1 15.10 1 47 0 0
#> 108.1 18.29 1 39 0 1
#> 39 15.59 1 37 0 1
#> 105 19.75 1 60 0 0
#> 30.1 17.43 1 78 0 0
#> 184.1 17.77 1 38 0 0
#> 101.1 9.97 1 10 0 1
#> 100 16.07 1 60 0 0
#> 154.1 12.63 1 20 1 0
#> 25.2 6.32 1 34 1 0
#> 96.1 14.54 1 33 0 1
#> 159 10.55 1 50 0 1
#> 130.3 16.47 1 53 0 1
#> 171 16.57 1 41 0 1
#> 42 12.43 1 49 0 1
#> 167 15.55 1 56 1 0
#> 41 18.02 1 40 1 0
#> 23.2 16.92 1 61 0 0
#> 159.1 10.55 1 50 0 1
#> 188 16.16 1 46 0 1
#> 96.2 14.54 1 33 0 1
#> 43 12.10 1 61 0 1
#> 30.2 17.43 1 78 0 0
#> 181 16.46 1 45 0 1
#> 50 10.02 1 NA 1 0
#> 188.1 16.16 1 46 0 1
#> 113.1 22.86 1 34 0 0
#> 136.1 21.83 1 43 0 1
#> 90.1 20.94 1 50 0 1
#> 111 17.45 1 47 0 1
#> 117 17.46 1 26 0 1
#> 188.2 16.16 1 46 0 1
#> 123 13.00 1 44 1 0
#> 153.1 21.33 1 55 1 0
#> 110 17.56 1 65 0 1
#> 4 17.64 1 NA 0 1
#> 130.4 16.47 1 53 0 1
#> 18 15.21 1 49 1 0
#> 187.2 9.92 1 39 1 0
#> 32 20.90 1 37 1 0
#> 161 24.00 0 45 0 0
#> 120 24.00 0 68 0 1
#> 104 24.00 0 50 1 0
#> 144 24.00 0 28 0 1
#> 138 24.00 0 44 1 0
#> 35 24.00 0 51 0 0
#> 144.1 24.00 0 28 0 1
#> 20 24.00 0 46 1 0
#> 20.1 24.00 0 46 1 0
#> 38 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 103 24.00 0 56 1 0
#> 137 24.00 0 45 1 0
#> 156 24.00 0 50 1 0
#> 20.2 24.00 0 46 1 0
#> 11 24.00 0 42 0 1
#> 174 24.00 0 49 1 0
#> 119 24.00 0 17 0 0
#> 74 24.00 0 43 0 1
#> 31 24.00 0 36 0 1
#> 75 24.00 0 21 1 0
#> 121 24.00 0 57 1 0
#> 148 24.00 0 61 1 0
#> 115 24.00 0 NA 1 0
#> 126 24.00 0 48 0 0
#> 126.1 24.00 0 48 0 0
#> 163 24.00 0 66 0 0
#> 31.1 24.00 0 36 0 1
#> 132 24.00 0 55 0 0
#> 115.1 24.00 0 NA 1 0
#> 121.1 24.00 0 57 1 0
#> 161.1 24.00 0 45 0 0
#> 120.1 24.00 0 68 0 1
#> 31.2 24.00 0 36 0 1
#> 35.1 24.00 0 51 0 0
#> 138.1 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 165 24.00 0 47 0 0
#> 44 24.00 0 56 0 0
#> 28 24.00 0 67 1 0
#> 162 24.00 0 51 0 0
#> 131 24.00 0 66 0 0
#> 161.2 24.00 0 45 0 0
#> 137.1 24.00 0 45 1 0
#> 165.1 24.00 0 47 0 0
#> 109 24.00 0 48 0 0
#> 98 24.00 0 34 1 0
#> 142 24.00 0 53 0 0
#> 83 24.00 0 6 0 0
#> 182 24.00 0 35 0 0
#> 156.1 24.00 0 50 1 0
#> 94 24.00 0 51 0 1
#> 47 24.00 0 38 0 1
#> 109.1 24.00 0 48 0 0
#> 118 24.00 0 44 1 0
#> 22 24.00 0 52 1 0
#> 64 24.00 0 43 0 0
#> 12 24.00 0 63 0 0
#> 31.3 24.00 0 36 0 1
#> 142.1 24.00 0 53 0 0
#> 121.2 24.00 0 57 1 0
#> 186 24.00 0 45 1 0
#> 176 24.00 0 43 0 1
#> 1 24.00 0 23 1 0
#> 71 24.00 0 51 0 0
#> 161.3 24.00 0 45 0 0
#> 151 24.00 0 42 0 0
#> 144.2 24.00 0 28 0 1
#> 20.3 24.00 0 46 1 0
#> 22.1 24.00 0 52 1 0
#> 33 24.00 0 53 0 0
#> 44.1 24.00 0 56 0 0
#> 118.1 24.00 0 44 1 0
#> 186.1 24.00 0 45 1 0
#> 75.1 24.00 0 21 1 0
#> 34 24.00 0 36 0 0
#> 193 24.00 0 45 0 1
#> 115.2 24.00 0 NA 1 0
#> 173 24.00 0 19 0 1
#> 73.1 24.00 0 NA 0 1
#> 44.2 24.00 0 56 0 0
#> 152 24.00 0 36 0 1
#> 120.2 24.00 0 68 0 1
#> 147 24.00 0 76 1 0
#> 103.1 24.00 0 56 1 0
#> 118.2 24.00 0 44 1 0
#> 28.1 24.00 0 67 1 0
#> 193.1 24.00 0 45 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.519 NA NA NA
#> 2 age, Cure model 0.0122 NA NA NA
#> 3 grade_ii, Cure model -0.288 NA NA NA
#> 4 grade_iii, Cure model 0.840 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00979 NA NA NA
#> 2 grade_ii, Survival model 0.829 NA NA NA
#> 3 grade_iii, Survival model 0.619 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.51889 0.01221 -0.28762 0.83973
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 260.4
#> Residual Deviance: 248.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.51888592 0.01221137 -0.28762008 0.83972562
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.009785648 0.829134565 0.619354538
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.869441104 0.702859743 0.635399605 0.712506896 0.948387643 0.922195185
#> [7] 0.869441104 0.538597433 0.411860060 0.043373582 0.204291498 0.824016852
#> [13] 0.833195958 0.974123271 0.616074028 0.778199851 0.094959613 0.471098879
#> [19] 0.842363265 0.166866311 0.411860060 0.325656772 0.113359610 0.084554835
#> [25] 0.148981905 0.286805825 0.922195185 0.974123271 0.471098879 0.296774983
#> [31] 0.431300734 0.654731193 0.009611494 0.913389393 0.204291498 0.759647912
#> [37] 0.796637572 0.258184009 0.064648228 0.248639134 0.166866311 0.528735493
#> [43] 0.140314848 0.431300734 0.204291498 0.851509376 0.258184009 0.895742768
#> [49] 0.335150780 0.258184009 0.382917728 0.654731193 0.017449066 0.204291498
#> [55] 0.471098879 0.895742768 0.204291498 0.674237764 0.741122504 0.922195185
#> [61] 0.033188041 0.194785008 0.043373582 0.586761478 0.991349899 0.157829127
#> [67] 0.948387643 0.731589198 0.001322068 0.635399605 0.296774983 0.596580739
#> [73] 0.185175614 0.382917728 0.335150780 0.851509376 0.576994077 0.741122504
#> [79] 0.948387643 0.674237764 0.805817946 0.471098879 0.461024128 0.768932279
#> [85] 0.606352811 0.316037555 0.431300734 0.805817946 0.548396436 0.674237764
#> [91] 0.787419935 0.382917728 0.518849990 0.548396436 0.017449066 0.064648228
#> [97] 0.113359610 0.373410523 0.363861312 0.548396436 0.722078913 0.094959613
#> [103] 0.354200460 0.471098879 0.625768040 0.869441104 0.131360954 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 187 57 157 60 25 77 187.1 79 45 169 55 10 93
#> 9.92 14.46 15.10 13.15 6.32 7.27 9.92 16.23 17.42 22.41 19.34 10.53 10.33
#> 91 29 49 153 130 145 166 45.1 134 90 197 68 8
#> 5.33 15.45 12.19 21.33 16.47 10.07 19.98 17.42 17.81 20.94 21.60 20.62 18.43
#> 77.1 91.1 130.1 108 23 180 92 70 58 37 107 179 136
#> 7.27 5.33 16.47 18.29 16.92 14.82 22.92 7.38 19.34 12.52 11.18 18.63 21.83
#> 76 166.1 5 190 23.1 55.1 101 179.1 16 184 179.2 30 180.1
#> 19.22 19.98 16.43 20.81 16.92 19.34 9.97 18.63 8.71 17.77 18.63 17.43 14.82
#> 113 55.2 130.2 16.1 55.3 96 154 77.2 15 170 169.1 6 127
#> 22.86 19.34 16.47 8.71 19.34 14.54 12.63 7.27 22.68 19.54 22.41 15.64 3.53
#> 150 25.1 14 168 157.1 108.1 39 105 30.1 184.1 101.1 100 154.1
#> 20.33 6.32 12.89 23.72 15.10 18.29 15.59 19.75 17.43 17.77 9.97 16.07 12.63
#> 25.2 96.1 159 130.3 171 42 167 41 23.2 159.1 188 96.2 43
#> 6.32 14.54 10.55 16.47 16.57 12.43 15.55 18.02 16.92 10.55 16.16 14.54 12.10
#> 30.2 181 188.1 113.1 136.1 90.1 111 117 188.2 123 153.1 110 130.4
#> 17.43 16.46 16.16 22.86 21.83 20.94 17.45 17.46 16.16 13.00 21.33 17.56 16.47
#> 18 187.2 32 161 120 104 144 138 35 144.1 20 20.1 38
#> 15.21 9.92 20.90 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 103 137 156 20.2 11 174 119 74 31 75 121 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 126.1 163 31.1 132 121.1 161.1 120.1 31.2 35.1 138.1 165 44
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 162 131 161.2 137.1 165.1 109 98 142 83 182 156.1 94
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47 109.1 118 22 64 12 31.3 142.1 121.2 186 176 1 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161.3 151 144.2 20.3 22.1 33 44.1 118.1 186.1 75.1 34 193 173
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44.2 152 120.2 147 103.1 118.2 28.1 193.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[43]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003988377 0.540465981 0.115744701
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.650569476 0.009814712 0.416774287
#> grade_iii, Cure model
#> 0.882821250
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 29 15.45 1 68 1 0
#> 155 13.08 1 26 0 0
#> 123 13.00 1 44 1 0
#> 107 11.18 1 54 1 0
#> 136 21.83 1 43 0 1
#> 179 18.63 1 42 0 0
#> 70 7.38 1 30 1 0
#> 58 19.34 1 39 0 0
#> 183 9.24 1 67 1 0
#> 183.1 9.24 1 67 1 0
#> 49 12.19 1 48 1 0
#> 197 21.60 1 69 1 0
#> 129 23.41 1 53 1 0
#> 93 10.33 1 52 0 1
#> 86 23.81 1 58 0 1
#> 105 19.75 1 60 0 0
#> 166 19.98 1 48 0 0
#> 171 16.57 1 41 0 1
#> 97 19.14 1 65 0 1
#> 29.1 15.45 1 68 1 0
#> 29.2 15.45 1 68 1 0
#> 184 17.77 1 38 0 0
#> 30 17.43 1 78 0 0
#> 175 21.91 1 43 0 0
#> 37 12.52 1 57 1 0
#> 192 16.44 1 31 1 0
#> 89 11.44 1 NA 0 0
#> 43 12.10 1 61 0 1
#> 92 22.92 1 47 0 1
#> 154 12.63 1 20 1 0
#> 56 12.21 1 60 0 0
#> 88 18.37 1 47 0 0
#> 69 23.23 1 25 0 1
#> 197.1 21.60 1 69 1 0
#> 45 17.42 1 54 0 1
#> 16 8.71 1 71 0 1
#> 15 22.68 1 48 0 0
#> 155.1 13.08 1 26 0 0
#> 96 14.54 1 33 0 1
#> 192.1 16.44 1 31 1 0
#> 170 19.54 1 43 0 1
#> 149 8.37 1 33 1 0
#> 111 17.45 1 47 0 1
#> 127 3.53 1 62 0 1
#> 24 23.89 1 38 0 0
#> 32 20.90 1 37 1 0
#> 23 16.92 1 61 0 0
#> 5 16.43 1 51 0 1
#> 190 20.81 1 42 1 0
#> 16.1 8.71 1 71 0 1
#> 66 22.13 1 53 0 0
#> 81 14.06 1 34 0 0
#> 105.1 19.75 1 60 0 0
#> 153 21.33 1 55 1 0
#> 125 15.65 1 67 1 0
#> 69.1 23.23 1 25 0 1
#> 59 10.16 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 169 22.41 1 46 0 0
#> 194 22.40 1 38 0 1
#> 32.1 20.90 1 37 1 0
#> 92.1 22.92 1 47 0 1
#> 154.1 12.63 1 20 1 0
#> 13 14.34 1 54 0 1
#> 5.1 16.43 1 51 0 1
#> 69.2 23.23 1 25 0 1
#> 127.1 3.53 1 62 0 1
#> 179.1 18.63 1 42 0 0
#> 139 21.49 1 63 1 0
#> 29.3 15.45 1 68 1 0
#> 170.1 19.54 1 43 0 1
#> 29.4 15.45 1 68 1 0
#> 100 16.07 1 60 0 0
#> 194.1 22.40 1 38 0 1
#> 184.1 17.77 1 38 0 0
#> 157 15.10 1 47 0 0
#> 180 14.82 1 37 0 0
#> 107.1 11.18 1 54 1 0
#> 4 17.64 1 NA 0 1
#> 42 12.43 1 49 0 1
#> 36 21.19 1 48 0 1
#> 96.1 14.54 1 33 0 1
#> 189 10.51 1 NA 1 0
#> 183.2 9.24 1 67 1 0
#> 79 16.23 1 54 1 0
#> 106 16.67 1 49 1 0
#> 139.1 21.49 1 63 1 0
#> 81.1 14.06 1 34 0 0
#> 59.1 10.16 1 NA 1 0
#> 181 16.46 1 45 0 1
#> 86.1 23.81 1 58 0 1
#> 149.1 8.37 1 33 1 0
#> 133 14.65 1 57 0 0
#> 197.2 21.60 1 69 1 0
#> 10 10.53 1 34 0 0
#> 90 20.94 1 50 0 1
#> 78.1 23.88 1 43 0 0
#> 59.2 10.16 1 NA 1 0
#> 134 17.81 1 47 1 0
#> 91 5.33 1 61 0 1
#> 101 9.97 1 10 0 1
#> 145 10.07 1 65 1 0
#> 169.1 22.41 1 46 0 0
#> 133.1 14.65 1 57 0 0
#> 14 12.89 1 21 0 0
#> 10.1 10.53 1 34 0 0
#> 159 10.55 1 50 0 1
#> 114 13.68 1 NA 0 0
#> 89.1 11.44 1 NA 0 0
#> 41 18.02 1 40 1 0
#> 183.3 9.24 1 67 1 0
#> 175.1 21.91 1 43 0 0
#> 132 24.00 0 55 0 0
#> 186 24.00 0 45 1 0
#> 87 24.00 0 27 0 0
#> 11 24.00 0 42 0 1
#> 131 24.00 0 66 0 0
#> 174 24.00 0 49 1 0
#> 196 24.00 0 19 0 0
#> 196.1 24.00 0 19 0 0
#> 196.2 24.00 0 19 0 0
#> 104 24.00 0 50 1 0
#> 74 24.00 0 43 0 1
#> 116 24.00 0 58 0 1
#> 1 24.00 0 23 1 0
#> 102 24.00 0 49 0 0
#> 46 24.00 0 71 0 0
#> 138 24.00 0 44 1 0
#> 196.3 24.00 0 19 0 0
#> 200 24.00 0 64 0 0
#> 34 24.00 0 36 0 0
#> 20 24.00 0 46 1 0
#> 80 24.00 0 41 0 0
#> 141 24.00 0 44 1 0
#> 33 24.00 0 53 0 0
#> 116.1 24.00 0 58 0 1
#> 12 24.00 0 63 0 0
#> 160 24.00 0 31 1 0
#> 46.1 24.00 0 71 0 0
#> 163 24.00 0 66 0 0
#> 104.1 24.00 0 50 1 0
#> 137 24.00 0 45 1 0
#> 152 24.00 0 36 0 1
#> 33.1 24.00 0 53 0 0
#> 44 24.00 0 56 0 0
#> 174.1 24.00 0 49 1 0
#> 146 24.00 0 63 1 0
#> 9 24.00 0 31 1 0
#> 160.1 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 142 24.00 0 53 0 0
#> 67 24.00 0 25 0 0
#> 19 24.00 0 57 0 1
#> 11.1 24.00 0 42 0 1
#> 126 24.00 0 48 0 0
#> 34.1 24.00 0 36 0 0
#> 1.1 24.00 0 23 1 0
#> 35 24.00 0 51 0 0
#> 31 24.00 0 36 0 1
#> 94 24.00 0 51 0 1
#> 138.1 24.00 0 44 1 0
#> 121 24.00 0 57 1 0
#> 185 24.00 0 44 1 0
#> 12.1 24.00 0 63 0 0
#> 109 24.00 0 48 0 0
#> 67.1 24.00 0 25 0 0
#> 185.1 24.00 0 44 1 0
#> 20.1 24.00 0 46 1 0
#> 64 24.00 0 43 0 0
#> 74.1 24.00 0 43 0 1
#> 148 24.00 0 61 1 0
#> 31.1 24.00 0 36 0 1
#> 95 24.00 0 68 0 1
#> 104.2 24.00 0 50 1 0
#> 156 24.00 0 50 1 0
#> 162 24.00 0 51 0 0
#> 104.3 24.00 0 50 1 0
#> 162.1 24.00 0 51 0 0
#> 35.1 24.00 0 51 0 0
#> 115 24.00 0 NA 1 0
#> 3 24.00 0 31 1 0
#> 62 24.00 0 71 0 0
#> 27 24.00 0 63 1 0
#> 33.2 24.00 0 53 0 0
#> 64.1 24.00 0 43 0 0
#> 120 24.00 0 68 0 1
#> 115.1 24.00 0 NA 1 0
#> 104.4 24.00 0 50 1 0
#> 47 24.00 0 38 0 1
#> 72 24.00 0 40 0 1
#> 3.1 24.00 0 31 1 0
#> 62.1 24.00 0 71 0 0
#> 112 24.00 0 61 0 0
#> 67.2 24.00 0 25 0 0
#> 17 24.00 0 38 0 1
#> 62.2 24.00 0 71 0 0
#> 74.2 24.00 0 43 0 1
#> 119 24.00 0 17 0 0
#> 62.3 24.00 0 71 0 0
#> 48 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.651 NA NA NA
#> 2 age, Cure model 0.00981 NA NA NA
#> 3 grade_ii, Cure model 0.417 NA NA NA
#> 4 grade_iii, Cure model 0.883 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00399 NA NA NA
#> 2 grade_ii, Survival model 0.540 NA NA NA
#> 3 grade_iii, Survival model 0.116 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.650569 0.009815 0.416774 0.882821
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 255.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.650569476 0.009814712 0.416774287 0.882821250
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003988377 0.540465981 0.115744701
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.69817397 0.79782050 0.81191578 0.87365125 0.33250019 0.52241540
#> [7] 0.97566176 0.50423514 0.92609570 0.92609570 0.86017285 0.34549339
#> [13] 0.13687720 0.90653302 0.09998263 0.46772099 0.45834289 0.62622147
#> [19] 0.51336188 0.69817397 0.69817397 0.56670536 0.59240987 0.30669281
#> [25] 0.83969880 0.64277700 0.86692336 0.19687974 0.82593957 0.85336469
#> [31] 0.54025384 0.15399031 0.34549339 0.60094547 0.95095251 0.22512537
#> [37] 0.79782050 0.76237608 0.64277700 0.48609209 0.96338305 0.58382915
#> [43] 0.98789063 0.02405416 0.42987708 0.60943376 0.65880358 0.44892414
#> [49] 0.95095251 0.29329071 0.78369797 0.46772099 0.39936963 0.69042553
#> [55] 0.15399031 0.05680792 0.23952476 0.26682113 0.42987708 0.19687974
#> [61] 0.82593957 0.77658591 0.65880358 0.15399031 0.98789063 0.52241540
#> [67] 0.37851075 0.69817397 0.48609209 0.69817397 0.68256750 0.26682113
#> [73] 0.56670536 0.73365634 0.74087953 0.87365125 0.84654181 0.40962997
#> [79] 0.76237608 0.92609570 0.67468493 0.61788960 0.37851075 0.78369797
#> [85] 0.63451778 0.09998263 0.96338305 0.74809154 0.34549339 0.89342117
#> [91] 0.41979874 0.05680792 0.55803461 0.98178442 0.91959905 0.91309466
#> [97] 0.23952476 0.74809154 0.81893030 0.89342117 0.88682690 0.54921716
#> [103] 0.92609570 0.30669281 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 29 155 123 107 136 179 70 58 183 183.1 49 197 129
#> 15.45 13.08 13.00 11.18 21.83 18.63 7.38 19.34 9.24 9.24 12.19 21.60 23.41
#> 93 86 105 166 171 97 29.1 29.2 184 30 175 37 192
#> 10.33 23.81 19.75 19.98 16.57 19.14 15.45 15.45 17.77 17.43 21.91 12.52 16.44
#> 43 92 154 56 88 69 197.1 45 16 15 155.1 96 192.1
#> 12.10 22.92 12.63 12.21 18.37 23.23 21.60 17.42 8.71 22.68 13.08 14.54 16.44
#> 170 149 111 127 24 32 23 5 190 16.1 66 81 105.1
#> 19.54 8.37 17.45 3.53 23.89 20.90 16.92 16.43 20.81 8.71 22.13 14.06 19.75
#> 153 125 69.1 78 169 194 32.1 92.1 154.1 13 5.1 69.2 127.1
#> 21.33 15.65 23.23 23.88 22.41 22.40 20.90 22.92 12.63 14.34 16.43 23.23 3.53
#> 179.1 139 29.3 170.1 29.4 100 194.1 184.1 157 180 107.1 42 36
#> 18.63 21.49 15.45 19.54 15.45 16.07 22.40 17.77 15.10 14.82 11.18 12.43 21.19
#> 96.1 183.2 79 106 139.1 81.1 181 86.1 149.1 133 197.2 10 90
#> 14.54 9.24 16.23 16.67 21.49 14.06 16.46 23.81 8.37 14.65 21.60 10.53 20.94
#> 78.1 134 91 101 145 169.1 133.1 14 10.1 159 41 183.3 175.1
#> 23.88 17.81 5.33 9.97 10.07 22.41 14.65 12.89 10.53 10.55 18.02 9.24 21.91
#> 132 186 87 11 131 174 196 196.1 196.2 104 74 116 1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 46 138 196.3 200 34 20 80 141 33 116.1 12 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46.1 163 104.1 137 152 33.1 44 174.1 146 9 160.1 151 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 19 11.1 126 34.1 1.1 35 31 94 138.1 121 185 12.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109 67.1 185.1 20.1 64 74.1 148 31.1 95 104.2 156 162 104.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162.1 35.1 3 62 27 33.2 64.1 120 104.4 47 72 3.1 62.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 67.2 17 62.2 74.2 119 62.3 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[44]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01130097 0.42178762 0.17293475
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.94701146 0.01669533 0.36252598
#> grade_iii, Cure model
#> 0.55458130
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 128 20.35 1 35 0 1
#> 133 14.65 1 57 0 0
#> 59 10.16 1 NA 1 0
#> 110 17.56 1 65 0 1
#> 92 22.92 1 47 0 1
#> 183 9.24 1 67 1 0
#> 187 9.92 1 39 1 0
#> 128.1 20.35 1 35 0 1
#> 70 7.38 1 30 1 0
#> 168 23.72 1 70 0 0
#> 145 10.07 1 65 1 0
#> 58 19.34 1 39 0 0
#> 129 23.41 1 53 1 0
#> 49 12.19 1 48 1 0
#> 113 22.86 1 34 0 0
#> 181 16.46 1 45 0 1
#> 58.1 19.34 1 39 0 0
#> 188 16.16 1 46 0 1
#> 177 12.53 1 75 0 0
#> 195 11.76 1 NA 1 0
#> 194 22.40 1 38 0 1
#> 183.1 9.24 1 67 1 0
#> 188.1 16.16 1 46 0 1
#> 59.1 10.16 1 NA 1 0
#> 63 22.77 1 31 1 0
#> 199 19.81 1 NA 0 1
#> 105 19.75 1 60 0 0
#> 50 10.02 1 NA 1 0
#> 41 18.02 1 40 1 0
#> 60 13.15 1 38 1 0
#> 179 18.63 1 42 0 0
#> 25 6.32 1 34 1 0
#> 107 11.18 1 54 1 0
#> 171 16.57 1 41 0 1
#> 85 16.44 1 36 0 0
#> 180 14.82 1 37 0 0
#> 86 23.81 1 58 0 1
#> 18 15.21 1 49 1 0
#> 18.1 15.21 1 49 1 0
#> 189 10.51 1 NA 1 0
#> 50.1 10.02 1 NA 1 0
#> 114 13.68 1 NA 0 0
#> 189.1 10.51 1 NA 1 0
#> 145.1 10.07 1 65 1 0
#> 197 21.60 1 69 1 0
#> 133.1 14.65 1 57 0 0
#> 155 13.08 1 26 0 0
#> 10 10.53 1 34 0 0
#> 96 14.54 1 33 0 1
#> 149 8.37 1 33 1 0
#> 8 18.43 1 32 0 0
#> 125 15.65 1 67 1 0
#> 168.1 23.72 1 70 0 0
#> 16 8.71 1 71 0 1
#> 29 15.45 1 68 1 0
#> 61 10.12 1 36 0 1
#> 114.1 13.68 1 NA 0 0
#> 106 16.67 1 49 1 0
#> 24 23.89 1 38 0 0
#> 99 21.19 1 38 0 1
#> 36 21.19 1 48 0 1
#> 110.1 17.56 1 65 0 1
#> 111 17.45 1 47 0 1
#> 184 17.77 1 38 0 0
#> 166 19.98 1 48 0 0
#> 56 12.21 1 60 0 0
#> 150 20.33 1 48 0 0
#> 52 10.42 1 52 0 1
#> 41.1 18.02 1 40 1 0
#> 92.1 22.92 1 47 0 1
#> 45 17.42 1 54 0 1
#> 105.1 19.75 1 60 0 0
#> 5 16.43 1 51 0 1
#> 195.1 11.76 1 NA 1 0
#> 6 15.64 1 39 0 0
#> 114.2 13.68 1 NA 0 0
#> 8.1 18.43 1 32 0 0
#> 117 17.46 1 26 0 1
#> 58.2 19.34 1 39 0 0
#> 117.1 17.46 1 26 0 1
#> 76 19.22 1 54 0 1
#> 5.1 16.43 1 51 0 1
#> 157 15.10 1 47 0 0
#> 96.1 14.54 1 33 0 1
#> 124 9.73 1 NA 1 0
#> 133.2 14.65 1 57 0 0
#> 188.2 16.16 1 46 0 1
#> 52.1 10.42 1 52 0 1
#> 99.1 21.19 1 38 0 1
#> 105.2 19.75 1 60 0 0
#> 139 21.49 1 63 1 0
#> 100 16.07 1 60 0 0
#> 58.3 19.34 1 39 0 0
#> 26 15.77 1 49 0 1
#> 96.2 14.54 1 33 0 1
#> 197.1 21.60 1 69 1 0
#> 159 10.55 1 50 0 1
#> 5.2 16.43 1 51 0 1
#> 180.1 14.82 1 37 0 0
#> 180.2 14.82 1 37 0 0
#> 114.3 13.68 1 NA 0 0
#> 101 9.97 1 10 0 1
#> 129.1 23.41 1 53 1 0
#> 199.1 19.81 1 NA 0 1
#> 77 7.27 1 67 0 1
#> 93 10.33 1 52 0 1
#> 154 12.63 1 20 1 0
#> 181.1 16.46 1 45 0 1
#> 155.1 13.08 1 26 0 0
#> 158 20.14 1 74 1 0
#> 114.4 13.68 1 NA 0 0
#> 140 12.68 1 59 1 0
#> 74 24.00 0 43 0 1
#> 116 24.00 0 58 0 1
#> 160 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 152 24.00 0 36 0 1
#> 198 24.00 0 66 0 1
#> 126 24.00 0 48 0 0
#> 147 24.00 0 76 1 0
#> 119 24.00 0 17 0 0
#> 102 24.00 0 49 0 0
#> 3 24.00 0 31 1 0
#> 131 24.00 0 66 0 0
#> 144 24.00 0 28 0 1
#> 21 24.00 0 47 0 0
#> 21.1 24.00 0 47 0 0
#> 161 24.00 0 45 0 0
#> 193 24.00 0 45 0 1
#> 196 24.00 0 19 0 0
#> 74.1 24.00 0 43 0 1
#> 115 24.00 0 NA 1 0
#> 46 24.00 0 71 0 0
#> 141 24.00 0 44 1 0
#> 193.1 24.00 0 45 0 1
#> 67 24.00 0 25 0 0
#> 7 24.00 0 37 1 0
#> 82 24.00 0 34 0 0
#> 146 24.00 0 63 1 0
#> 67.1 24.00 0 25 0 0
#> 71 24.00 0 51 0 0
#> 31 24.00 0 36 0 1
#> 74.2 24.00 0 43 0 1
#> 191 24.00 0 60 0 1
#> 46.1 24.00 0 71 0 0
#> 44 24.00 0 56 0 0
#> 17 24.00 0 38 0 1
#> 67.2 24.00 0 25 0 0
#> 152.1 24.00 0 36 0 1
#> 54 24.00 0 53 1 0
#> 84 24.00 0 39 0 1
#> 121 24.00 0 57 1 0
#> 109 24.00 0 48 0 0
#> 83 24.00 0 6 0 0
#> 196.1 24.00 0 19 0 0
#> 82.1 24.00 0 34 0 0
#> 196.2 24.00 0 19 0 0
#> 65 24.00 0 57 1 0
#> 142 24.00 0 53 0 0
#> 11 24.00 0 42 0 1
#> 196.3 24.00 0 19 0 0
#> 120 24.00 0 68 0 1
#> 82.2 24.00 0 34 0 0
#> 144.1 24.00 0 28 0 1
#> 119.1 24.00 0 17 0 0
#> 17.1 24.00 0 38 0 1
#> 71.1 24.00 0 51 0 0
#> 118 24.00 0 44 1 0
#> 172 24.00 0 41 0 0
#> 147.1 24.00 0 76 1 0
#> 75 24.00 0 21 1 0
#> 102.1 24.00 0 49 0 0
#> 83.1 24.00 0 6 0 0
#> 80 24.00 0 41 0 0
#> 84.1 24.00 0 39 0 1
#> 144.2 24.00 0 28 0 1
#> 135 24.00 0 58 1 0
#> 112 24.00 0 61 0 0
#> 151 24.00 0 42 0 0
#> 72 24.00 0 40 0 1
#> 112.1 24.00 0 61 0 0
#> 64 24.00 0 43 0 0
#> 147.2 24.00 0 76 1 0
#> 165 24.00 0 47 0 0
#> 120.1 24.00 0 68 0 1
#> 64.1 24.00 0 43 0 0
#> 160.1 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 71.2 24.00 0 51 0 0
#> 53 24.00 0 32 0 1
#> 33 24.00 0 53 0 0
#> 17.2 24.00 0 38 0 1
#> 198.1 24.00 0 66 0 1
#> 141.1 24.00 0 44 1 0
#> 20 24.00 0 46 1 0
#> 11.1 24.00 0 42 0 1
#> 185.1 24.00 0 44 1 0
#> 21.2 24.00 0 47 0 0
#> 35 24.00 0 51 0 0
#> 138.1 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.947 NA NA NA
#> 2 age, Cure model 0.0167 NA NA NA
#> 3 grade_ii, Cure model 0.363 NA NA NA
#> 4 grade_iii, Cure model 0.555 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0113 NA NA NA
#> 2 grade_ii, Survival model 0.422 NA NA NA
#> 3 grade_iii, Survival model 0.173 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.9470 0.0167 0.3625 0.5546
#>
#> Degrees of Freedom: 182 Total (i.e. Null); 179 Residual
#> Null Deviance: 253.2
#> Residual Deviance: 247.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.94701146 0.01669533 0.36252598 0.55458130
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01130097 0.42178762 0.17293475
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.0895586199 0.5655862681 0.2516920277 0.0223830967 0.9001685092
#> [6] 0.8860836502 0.0895586199 0.9569774137 0.0053080464 0.8440414122
#> [11] 0.1508203457 0.0133143154 0.7343794987 0.0327665034 0.3341922525
#> [16] 0.1508203457 0.3994308379 0.7075823382 0.0447399649 0.9001685092
#> [21] 0.3994308379 0.0387864619 0.1265629017 0.2226818877 0.6419408023
#> [26] 0.1941251741 0.9856333066 0.7478674928 0.3235218916 0.3555756890
#> [31] 0.5288010658 0.0024124498 0.4925474521 0.4925474521 0.8440414122
#> [36] 0.0508792667 0.5655862681 0.6550056700 0.7750057648 0.6035443408
#> [41] 0.9426778214 0.2036156463 0.4566118690 0.0053080464 0.9283673646
#> [46] 0.4804739915 0.8300682880 0.3129395226 0.0005190529 0.0699804666
#> [51] 0.0699804666 0.2516920277 0.2919914815 0.2417978762 0.1186975469
#> [56] 0.7209196099 0.1035666829 0.7886907879 0.2226818877 0.0223830967
#> [61] 0.3024012383 0.1265629017 0.3665451474 0.4684887741 0.2036156463
#> [66] 0.2717563906 0.1508203457 0.2717563906 0.1848069079 0.3665451474
#> [71] 0.5165422667 0.6035443408 0.5655862681 0.3994308379 0.7886907879
#> [76] 0.0699804666 0.1265629017 0.0632718691 0.4331309810 0.1508203457
#> [81] 0.4448223523 0.6035443408 0.0508792667 0.7613974070 0.3665451474
#> [86] 0.5288010658 0.5288010658 0.8720029973 0.0133143154 0.9712585988
#> [91] 0.8161440537 0.6943872222 0.3341922525 0.6550056700 0.1110446130
#> [96] 0.6811376704 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [101] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 128 133 110 92 183 187 128.1 70 168 145 58 129 49
#> 20.35 14.65 17.56 22.92 9.24 9.92 20.35 7.38 23.72 10.07 19.34 23.41 12.19
#> 113 181 58.1 188 177 194 183.1 188.1 63 105 41 60 179
#> 22.86 16.46 19.34 16.16 12.53 22.40 9.24 16.16 22.77 19.75 18.02 13.15 18.63
#> 25 107 171 85 180 86 18 18.1 145.1 197 133.1 155 10
#> 6.32 11.18 16.57 16.44 14.82 23.81 15.21 15.21 10.07 21.60 14.65 13.08 10.53
#> 96 149 8 125 168.1 16 29 61 106 24 99 36 110.1
#> 14.54 8.37 18.43 15.65 23.72 8.71 15.45 10.12 16.67 23.89 21.19 21.19 17.56
#> 111 184 166 56 150 52 41.1 92.1 45 105.1 5 6 8.1
#> 17.45 17.77 19.98 12.21 20.33 10.42 18.02 22.92 17.42 19.75 16.43 15.64 18.43
#> 117 58.2 117.1 76 5.1 157 96.1 133.2 188.2 52.1 99.1 105.2 139
#> 17.46 19.34 17.46 19.22 16.43 15.10 14.54 14.65 16.16 10.42 21.19 19.75 21.49
#> 100 58.3 26 96.2 197.1 159 5.2 180.1 180.2 101 129.1 77 93
#> 16.07 19.34 15.77 14.54 21.60 10.55 16.43 14.82 14.82 9.97 23.41 7.27 10.33
#> 154 181.1 155.1 158 140 74 116 160 138 152 198 126 147
#> 12.63 16.46 13.08 20.14 12.68 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119 102 3 131 144 21 21.1 161 193 196 74.1 46 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193.1 67 7 82 146 67.1 71 31 74.2 191 46.1 44 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67.2 152.1 54 84 121 109 83 196.1 82.1 196.2 65 142 11
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196.3 120 82.2 144.1 119.1 17.1 71.1 118 172 147.1 75 102.1 83.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 84.1 144.2 135 112 151 72 112.1 64 147.2 165 120.1 64.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160.1 185 71.2 53 33 17.2 198.1 141.1 20 11.1 185.1 21.2 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138.1
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[45]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003763058 0.265806533 0.068744360
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.01359129 0.02270931 0.29605261
#> grade_iii, Cure model
#> 0.21306266
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 159 10.55 1 50 0 1
#> 29 15.45 1 68 1 0
#> 77 7.27 1 67 0 1
#> 133 14.65 1 57 0 0
#> 145 10.07 1 65 1 0
#> 85 16.44 1 36 0 0
#> 139 21.49 1 63 1 0
#> 159.1 10.55 1 50 0 1
#> 66 22.13 1 53 0 0
#> 166 19.98 1 48 0 0
#> 56 12.21 1 60 0 0
#> 92 22.92 1 47 0 1
#> 63 22.77 1 31 1 0
#> 70 7.38 1 30 1 0
#> 81 14.06 1 34 0 0
#> 6 15.64 1 39 0 0
#> 159.2 10.55 1 50 0 1
#> 97 19.14 1 65 0 1
#> 125 15.65 1 67 1 0
#> 192 16.44 1 31 1 0
#> 18 15.21 1 49 1 0
#> 187 9.92 1 39 1 0
#> 113 22.86 1 34 0 0
#> 124 9.73 1 NA 1 0
#> 179 18.63 1 42 0 0
#> 43 12.10 1 61 0 1
#> 133.1 14.65 1 57 0 0
#> 157 15.10 1 47 0 0
#> 41 18.02 1 40 1 0
#> 181 16.46 1 45 0 1
#> 105 19.75 1 60 0 0
#> 170 19.54 1 43 0 1
#> 157.1 15.10 1 47 0 0
#> 81.1 14.06 1 34 0 0
#> 155 13.08 1 26 0 0
#> 14 12.89 1 21 0 0
#> 169 22.41 1 46 0 0
#> 170.1 19.54 1 43 0 1
#> 52 10.42 1 52 0 1
#> 5 16.43 1 51 0 1
#> 85.1 16.44 1 36 0 0
#> 166.1 19.98 1 48 0 0
#> 164 23.60 1 76 0 1
#> 140 12.68 1 59 1 0
#> 18.1 15.21 1 49 1 0
#> 86 23.81 1 58 0 1
#> 76 19.22 1 54 0 1
#> 192.1 16.44 1 31 1 0
#> 39 15.59 1 37 0 1
#> 123 13.00 1 44 1 0
#> 91 5.33 1 61 0 1
#> 171 16.57 1 41 0 1
#> 18.2 15.21 1 49 1 0
#> 88 18.37 1 47 0 0
#> 57 14.46 1 45 0 1
#> 49 12.19 1 48 1 0
#> 157.2 15.10 1 47 0 0
#> 77.1 7.27 1 67 0 1
#> 100 16.07 1 60 0 0
#> 154 12.63 1 20 1 0
#> 181.1 16.46 1 45 0 1
#> 29.1 15.45 1 68 1 0
#> 91.1 5.33 1 61 0 1
#> 105.1 19.75 1 60 0 0
#> 41.1 18.02 1 40 1 0
#> 139.1 21.49 1 63 1 0
#> 190 20.81 1 42 1 0
#> 133.2 14.65 1 57 0 0
#> 197 21.60 1 69 1 0
#> 171.1 16.57 1 41 0 1
#> 108 18.29 1 39 0 1
#> 63.1 22.77 1 31 1 0
#> 195 11.76 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 113.1 22.86 1 34 0 0
#> 49.1 12.19 1 48 1 0
#> 110 17.56 1 65 0 1
#> 8 18.43 1 32 0 0
#> 134 17.81 1 47 1 0
#> 180 14.82 1 37 0 0
#> 30 17.43 1 78 0 0
#> 60 13.15 1 38 1 0
#> 127 3.53 1 62 0 1
#> 199 19.81 1 NA 0 1
#> 129 23.41 1 53 1 0
#> 92.1 22.92 1 47 0 1
#> 52.1 10.42 1 52 0 1
#> 183 9.24 1 67 1 0
#> 125.1 15.65 1 67 1 0
#> 107 11.18 1 54 1 0
#> 100.1 16.07 1 60 0 0
#> 55 19.34 1 69 0 1
#> 153 21.33 1 55 1 0
#> 168 23.72 1 70 0 0
#> 91.2 5.33 1 61 0 1
#> 130 16.47 1 53 0 1
#> 93 10.33 1 52 0 1
#> 192.2 16.44 1 31 1 0
#> 168.1 23.72 1 70 0 0
#> 175 21.91 1 43 0 0
#> 124.1 9.73 1 NA 1 0
#> 56.1 12.21 1 60 0 0
#> 85.2 16.44 1 36 0 0
#> 105.2 19.75 1 60 0 0
#> 92.2 22.92 1 47 0 1
#> 18.3 15.21 1 49 1 0
#> 32 20.90 1 37 1 0
#> 79 16.23 1 54 1 0
#> 183.1 9.24 1 67 1 0
#> 187.1 9.92 1 39 1 0
#> 153.1 21.33 1 55 1 0
#> 6.1 15.64 1 39 0 0
#> 27 24.00 0 63 1 0
#> 34 24.00 0 36 0 0
#> 120 24.00 0 68 0 1
#> 103 24.00 0 56 1 0
#> 80 24.00 0 41 0 0
#> 121 24.00 0 57 1 0
#> 94 24.00 0 51 0 1
#> 28 24.00 0 67 1 0
#> 191 24.00 0 60 0 1
#> 137 24.00 0 45 1 0
#> 112 24.00 0 61 0 0
#> 142 24.00 0 53 0 0
#> 186 24.00 0 45 1 0
#> 143 24.00 0 51 0 0
#> 1 24.00 0 23 1 0
#> 2 24.00 0 9 0 0
#> 47 24.00 0 38 0 1
#> 193 24.00 0 45 0 1
#> 131 24.00 0 66 0 0
#> 9 24.00 0 31 1 0
#> 20 24.00 0 46 1 0
#> 34.1 24.00 0 36 0 0
#> 109 24.00 0 48 0 0
#> 98 24.00 0 34 1 0
#> 62 24.00 0 71 0 0
#> 185 24.00 0 44 1 0
#> 196 24.00 0 19 0 0
#> 12 24.00 0 63 0 0
#> 146 24.00 0 63 1 0
#> 121.1 24.00 0 57 1 0
#> 198 24.00 0 66 0 1
#> 87 24.00 0 27 0 0
#> 176 24.00 0 43 0 1
#> 142.1 24.00 0 53 0 0
#> 72 24.00 0 40 0 1
#> 163 24.00 0 66 0 0
#> 161 24.00 0 45 0 0
#> 126 24.00 0 48 0 0
#> 64 24.00 0 43 0 0
#> 84 24.00 0 39 0 1
#> 73 24.00 0 NA 0 1
#> 193.1 24.00 0 45 0 1
#> 73.1 24.00 0 NA 0 1
#> 64.1 24.00 0 43 0 0
#> 182 24.00 0 35 0 0
#> 11 24.00 0 42 0 1
#> 75 24.00 0 21 1 0
#> 38 24.00 0 31 1 0
#> 161.1 24.00 0 45 0 0
#> 11.1 24.00 0 42 0 1
#> 82 24.00 0 34 0 0
#> 44 24.00 0 56 0 0
#> 104 24.00 0 50 1 0
#> 20.1 24.00 0 46 1 0
#> 84.1 24.00 0 39 0 1
#> 152 24.00 0 36 0 1
#> 35 24.00 0 51 0 0
#> 2.1 24.00 0 9 0 0
#> 17 24.00 0 38 0 1
#> 34.2 24.00 0 36 0 0
#> 48 24.00 0 31 1 0
#> 132 24.00 0 55 0 0
#> 137.1 24.00 0 45 1 0
#> 47.1 24.00 0 38 0 1
#> 64.2 24.00 0 43 0 0
#> 176.1 24.00 0 43 0 1
#> 87.1 24.00 0 27 0 0
#> 103.1 24.00 0 56 1 0
#> 142.2 24.00 0 53 0 0
#> 104.1 24.00 0 50 1 0
#> 95 24.00 0 68 0 1
#> 74 24.00 0 43 0 1
#> 193.2 24.00 0 45 0 1
#> 141 24.00 0 44 1 0
#> 112.1 24.00 0 61 0 0
#> 122 24.00 0 66 0 0
#> 165 24.00 0 47 0 0
#> 2.2 24.00 0 9 0 0
#> 95.1 24.00 0 68 0 1
#> 138 24.00 0 44 1 0
#> 182.1 24.00 0 35 0 0
#> 11.2 24.00 0 42 0 1
#> 191.1 24.00 0 60 0 1
#> 120.1 24.00 0 68 0 1
#> 1.1 24.00 0 23 1 0
#> 160 24.00 0 31 1 0
#> 9.1 24.00 0 31 1 0
#> 27.1 24.00 0 63 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.01 NA NA NA
#> 2 age, Cure model 0.0227 NA NA NA
#> 3 grade_ii, Cure model 0.296 NA NA NA
#> 4 grade_iii, Cure model 0.213 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00376 NA NA NA
#> 2 grade_ii, Survival model 0.266 NA NA NA
#> 3 grade_iii, Survival model 0.0687 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.01359 0.02271 0.29605 0.21306
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 266.4
#> Residual Deviance: 261.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.01359129 0.02270931 0.29605261 0.21306266
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003763058 0.265806533 0.068744360
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.825240221 0.557434771 0.941635843 0.651475195 0.883341483 0.418201220
#> [7] 0.145103654 0.825240221 0.118057754 0.197557861 0.767218859 0.051569814
#> [13] 0.092484204 0.931906441 0.689753673 0.528877279 0.825240221 0.277668851
#> [19] 0.509994821 0.418201220 0.576428652 0.893119783 0.075250617 0.286957634
#> [25] 0.805817813 0.651475195 0.613587166 0.324504735 0.399339948 0.215002877
#> [31] 0.241268028 0.613587166 0.689753673 0.718742261 0.738144350 0.109226321
#> [37] 0.241268028 0.854134917 0.472162201 0.418201220 0.197557861 0.024679441
#> [43] 0.747848270 0.576428652 0.003355715 0.268429931 0.418201220 0.547852272
#> [49] 0.728450115 0.961061041 0.371123263 0.576428652 0.305657071 0.680071559
#> [55] 0.786539376 0.613587166 0.941635843 0.491102809 0.757546560 0.399339948
#> [61] 0.557434771 0.961061041 0.215002877 0.324504735 0.145103654 0.188765555
#> [67] 0.651475195 0.136058843 0.371123263 0.315070316 0.092484204 0.042620111
#> [73] 0.075250617 0.786539376 0.352307153 0.296290606 0.342970314 0.641882672
#> [79] 0.361684079 0.709046615 0.990181639 0.033723895 0.051569814 0.854134917
#> [85] 0.912515943 0.509994821 0.815532752 0.491102809 0.259230874 0.162570627
#> [91] 0.010718094 0.961061041 0.389838794 0.873560864 0.418201220 0.010718094
#> [97] 0.127010542 0.767218859 0.418201220 0.215002877 0.051569814 0.576428652
#> [103] 0.179926489 0.481638517 0.912515943 0.893119783 0.162570627 0.528877279
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000 0.000000000
#>
#> $Time
#> 159 29 77 133 145 85 139 159.1 66 166 56 92 63
#> 10.55 15.45 7.27 14.65 10.07 16.44 21.49 10.55 22.13 19.98 12.21 22.92 22.77
#> 70 81 6 159.2 97 125 192 18 187 113 179 43 133.1
#> 7.38 14.06 15.64 10.55 19.14 15.65 16.44 15.21 9.92 22.86 18.63 12.10 14.65
#> 157 41 181 105 170 157.1 81.1 155 14 169 170.1 52 5
#> 15.10 18.02 16.46 19.75 19.54 15.10 14.06 13.08 12.89 22.41 19.54 10.42 16.43
#> 85.1 166.1 164 140 18.1 86 76 192.1 39 123 91 171 18.2
#> 16.44 19.98 23.60 12.68 15.21 23.81 19.22 16.44 15.59 13.00 5.33 16.57 15.21
#> 88 57 49 157.2 77.1 100 154 181.1 29.1 91.1 105.1 41.1 139.1
#> 18.37 14.46 12.19 15.10 7.27 16.07 12.63 16.46 15.45 5.33 19.75 18.02 21.49
#> 190 133.2 197 171.1 108 63.1 69 113.1 49.1 110 8 134 180
#> 20.81 14.65 21.60 16.57 18.29 22.77 23.23 22.86 12.19 17.56 18.43 17.81 14.82
#> 30 60 127 129 92.1 52.1 183 125.1 107 100.1 55 153 168
#> 17.43 13.15 3.53 23.41 22.92 10.42 9.24 15.65 11.18 16.07 19.34 21.33 23.72
#> 91.2 130 93 192.2 168.1 175 56.1 85.2 105.2 92.2 18.3 32 79
#> 5.33 16.47 10.33 16.44 23.72 21.91 12.21 16.44 19.75 22.92 15.21 20.90 16.23
#> 183.1 187.1 153.1 6.1 27 34 120 103 80 121 94 28 191
#> 9.24 9.92 21.33 15.64 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 112 142 186 143 1 2 47 193 131 9 20 34.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109 98 62 185 196 12 146 121.1 198 87 176 142.1 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163 161 126 64 84 193.1 64.1 182 11 75 38 161.1 11.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82 44 104 20.1 84.1 152 35 2.1 17 34.2 48 132 137.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47.1 64.2 176.1 87.1 103.1 142.2 104.1 95 74 193.2 141 112.1 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 2.2 95.1 138 182.1 11.2 191.1 120.1 1.1 160 9.1 27.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[46]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01592097 0.95487629 0.58687686
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.773733296 0.006306762 0.724304723
#> grade_iii, Cure model
#> 1.149211922
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 179 18.63 1 42 0 0
#> 179.1 18.63 1 42 0 0
#> 15 22.68 1 48 0 0
#> 129 23.41 1 53 1 0
#> 29 15.45 1 68 1 0
#> 106 16.67 1 49 1 0
#> 181 16.46 1 45 0 1
#> 4 17.64 1 NA 0 1
#> 169 22.41 1 46 0 0
#> 197 21.60 1 69 1 0
#> 129.1 23.41 1 53 1 0
#> 164 23.60 1 76 0 1
#> 117 17.46 1 26 0 1
#> 123 13.00 1 44 1 0
#> 149 8.37 1 33 1 0
#> 150 20.33 1 48 0 0
#> 14 12.89 1 21 0 0
#> 189 10.51 1 NA 1 0
#> 139 21.49 1 63 1 0
#> 58 19.34 1 39 0 0
#> 168 23.72 1 70 0 0
#> 127 3.53 1 62 0 1
#> 169.1 22.41 1 46 0 0
#> 134 17.81 1 47 1 0
#> 32 20.90 1 37 1 0
#> 167 15.55 1 56 1 0
#> 139.1 21.49 1 63 1 0
#> 66 22.13 1 53 0 0
#> 89 11.44 1 NA 0 0
#> 130 16.47 1 53 0 1
#> 154 12.63 1 20 1 0
#> 101 9.97 1 10 0 1
#> 13 14.34 1 54 0 1
#> 37 12.52 1 57 1 0
#> 4.1 17.64 1 NA 0 1
#> 153 21.33 1 55 1 0
#> 136 21.83 1 43 0 1
#> 197.1 21.60 1 69 1 0
#> 45 17.42 1 54 0 1
#> 25 6.32 1 34 1 0
#> 90 20.94 1 50 0 1
#> 23 16.92 1 61 0 0
#> 183 9.24 1 67 1 0
#> 194 22.40 1 38 0 1
#> 113 22.86 1 34 0 0
#> 41 18.02 1 40 1 0
#> 16 8.71 1 71 0 1
#> 145 10.07 1 65 1 0
#> 99 21.19 1 38 0 1
#> 89.1 11.44 1 NA 0 0
#> 61 10.12 1 36 0 1
#> 113.1 22.86 1 34 0 0
#> 25.1 6.32 1 34 1 0
#> 70 7.38 1 30 1 0
#> 99.1 21.19 1 38 0 1
#> 14.1 12.89 1 21 0 0
#> 69 23.23 1 25 0 1
#> 136.1 21.83 1 43 0 1
#> 150.1 20.33 1 48 0 0
#> 4.2 17.64 1 NA 0 1
#> 89.2 11.44 1 NA 0 0
#> 45.1 17.42 1 54 0 1
#> 187 9.92 1 39 1 0
#> 77 7.27 1 67 0 1
#> 106.1 16.67 1 49 1 0
#> 55 19.34 1 69 0 1
#> 187.1 9.92 1 39 1 0
#> 187.2 9.92 1 39 1 0
#> 106.2 16.67 1 49 1 0
#> 188 16.16 1 46 0 1
#> 13.1 14.34 1 54 0 1
#> 188.1 16.16 1 46 0 1
#> 188.2 16.16 1 46 0 1
#> 130.1 16.47 1 53 0 1
#> 123.1 13.00 1 44 1 0
#> 189.1 10.51 1 NA 1 0
#> 32.1 20.90 1 37 1 0
#> 170 19.54 1 43 0 1
#> 99.2 21.19 1 38 0 1
#> 97 19.14 1 65 0 1
#> 181.1 16.46 1 45 0 1
#> 39 15.59 1 37 0 1
#> 114 13.68 1 NA 0 0
#> 23.1 16.92 1 61 0 0
#> 99.3 21.19 1 38 0 1
#> 70.1 7.38 1 30 1 0
#> 88 18.37 1 47 0 0
#> 13.2 14.34 1 54 0 1
#> 190 20.81 1 42 1 0
#> 78 23.88 1 43 0 0
#> 88.1 18.37 1 47 0 0
#> 149.1 8.37 1 33 1 0
#> 92 22.92 1 47 0 1
#> 76 19.22 1 54 0 1
#> 124 9.73 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 76.1 19.22 1 54 0 1
#> 89.3 11.44 1 NA 0 0
#> 70.2 7.38 1 30 1 0
#> 184 17.77 1 38 0 0
#> 90.1 20.94 1 50 0 1
#> 61.1 10.12 1 36 0 1
#> 57 14.46 1 45 0 1
#> 6 15.64 1 39 0 0
#> 106.3 16.67 1 49 1 0
#> 110 17.56 1 65 0 1
#> 183.1 9.24 1 67 1 0
#> 159 10.55 1 50 0 1
#> 128 20.35 1 35 0 1
#> 167.1 15.55 1 56 1 0
#> 145.1 10.07 1 65 1 0
#> 43 12.10 1 61 0 1
#> 46 24.00 0 71 0 0
#> 178 24.00 0 52 1 0
#> 146 24.00 0 63 1 0
#> 44 24.00 0 56 0 0
#> 46.1 24.00 0 71 0 0
#> 102 24.00 0 49 0 0
#> 21 24.00 0 47 0 0
#> 95 24.00 0 68 0 1
#> 12 24.00 0 63 0 0
#> 152 24.00 0 36 0 1
#> 3 24.00 0 31 1 0
#> 152.1 24.00 0 36 0 1
#> 162 24.00 0 51 0 0
#> 198 24.00 0 66 0 1
#> 144 24.00 0 28 0 1
#> 7 24.00 0 37 1 0
#> 135 24.00 0 58 1 0
#> 9 24.00 0 31 1 0
#> 82 24.00 0 34 0 0
#> 173 24.00 0 19 0 1
#> 9.1 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 28 24.00 0 67 1 0
#> 161 24.00 0 45 0 0
#> 103 24.00 0 56 1 0
#> 173.1 24.00 0 19 0 1
#> 46.2 24.00 0 71 0 0
#> 142 24.00 0 53 0 0
#> 141 24.00 0 44 1 0
#> 28.1 24.00 0 67 1 0
#> 173.2 24.00 0 19 0 1
#> 198.1 24.00 0 66 0 1
#> 7.1 24.00 0 37 1 0
#> 151 24.00 0 42 0 0
#> 19 24.00 0 57 0 1
#> 143 24.00 0 51 0 0
#> 64 24.00 0 43 0 0
#> 20 24.00 0 46 1 0
#> 160 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 182 24.00 0 35 0 0
#> 65 24.00 0 57 1 0
#> 2 24.00 0 9 0 0
#> 115 24.00 0 NA 1 0
#> 3.1 24.00 0 31 1 0
#> 48 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 119 24.00 0 17 0 0
#> 122.1 24.00 0 66 0 0
#> 144.1 24.00 0 28 0 1
#> 143.1 24.00 0 51 0 0
#> 73 24.00 0 NA 0 1
#> 53 24.00 0 32 0 1
#> 47 24.00 0 38 0 1
#> 193 24.00 0 45 0 1
#> 35 24.00 0 51 0 0
#> 121 24.00 0 57 1 0
#> 44.1 24.00 0 56 0 0
#> 120 24.00 0 68 0 1
#> 1 24.00 0 23 1 0
#> 9.2 24.00 0 31 1 0
#> 83 24.00 0 6 0 0
#> 178.1 24.00 0 52 1 0
#> 141.1 24.00 0 44 1 0
#> 137 24.00 0 45 1 0
#> 11 24.00 0 42 0 1
#> 73.1 24.00 0 NA 0 1
#> 172 24.00 0 41 0 0
#> 21.1 24.00 0 47 0 0
#> 112 24.00 0 61 0 0
#> 116 24.00 0 58 0 1
#> 165 24.00 0 47 0 0
#> 152.2 24.00 0 36 0 1
#> 95.1 24.00 0 68 0 1
#> 2.1 24.00 0 9 0 0
#> 132 24.00 0 55 0 0
#> 64.1 24.00 0 43 0 0
#> 19.1 24.00 0 57 0 1
#> 109 24.00 0 48 0 0
#> 151.1 24.00 0 42 0 0
#> 22 24.00 0 52 1 0
#> 161.1 24.00 0 45 0 0
#> 104 24.00 0 50 1 0
#> 9.3 24.00 0 31 1 0
#> 174.1 24.00 0 49 1 0
#> 185 24.00 0 44 1 0
#> 131 24.00 0 66 0 0
#> 120.1 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.774 NA NA NA
#> 2 age, Cure model 0.00631 NA NA NA
#> 3 grade_ii, Cure model 0.724 NA NA NA
#> 4 grade_iii, Cure model 1.15 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0159 NA NA NA
#> 2 grade_ii, Survival model 0.955 NA NA NA
#> 3 grade_iii, Survival model 0.587 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.773733 0.006307 0.724305 1.149212
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.5
#> Residual Deviance: 246.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.773733296 0.006306762 0.724304723 1.149211922
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01592097 0.95487629 0.58687686
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.3261452538 0.3261452538 0.0525340295 0.0153181051 0.6368843230
#> [6] 0.4740087453 0.5378579762 0.0602556594 0.1129418025 0.0153181051
#> [11] 0.0073771645 0.4095133955 0.6927557280 0.9038867713 0.2495574163
#> [16] 0.7150430913 0.1314007448 0.2775455498 0.0022189110 0.9893288833
#> [21] 0.0602556594 0.3778485346 0.2133526093 0.6147491437 0.1314007448
#> [26] 0.0855576888 0.5161391774 0.7375296815 0.8270703367 0.6592858355
#> [31] 0.7487072264 0.1499865581 0.0948834495 0.1129418025 0.4307810378
#> [36] 0.9681765958 0.1946097725 0.4520738765 0.8708620325 0.0767777431
#> [41] 0.0391922613 0.3673469752 0.8927947422 0.8046871604 0.1595365305
#> [46] 0.7823517795 0.0391922613 0.9681765958 0.9256499680 0.1595365305
#> [51] 0.7150430913 0.0266833033 0.0948834495 0.2495574163 0.4307810378
#> [56] 0.8382573499 0.9574210353 0.4740087453 0.2775455498 0.8382573499
#> [61] 0.8382573499 0.4740087453 0.5596839843 0.6592858355 0.5596839843
#> [66] 0.5596839843 0.5161391774 0.6927557280 0.2133526093 0.2680849385
#> [71] 0.1595365305 0.3161515047 0.5378579762 0.6035535517 0.4520738765
#> [76] 0.1595365305 0.9256499680 0.3464234090 0.6592858355 0.2313967524
#> [81] 0.0003054513 0.3464234090 0.9038867713 0.0328474980 0.2966984224
#> [86] 0.4201271513 0.2966984224 0.9256499680 0.3882835629 0.1946097725
#> [91] 0.7823517795 0.6480733146 0.5923584218 0.4740087453 0.3988474707
#> [96] 0.8708620325 0.7710987751 0.2404822212 0.6147491437 0.8046871604
#> [101] 0.7598766834 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000
#>
#> $Time
#> 179 179.1 15 129 29 106 181 169 197 129.1 164 117 123
#> 18.63 18.63 22.68 23.41 15.45 16.67 16.46 22.41 21.60 23.41 23.60 17.46 13.00
#> 149 150 14 139 58 168 127 169.1 134 32 167 139.1 66
#> 8.37 20.33 12.89 21.49 19.34 23.72 3.53 22.41 17.81 20.90 15.55 21.49 22.13
#> 130 154 101 13 37 153 136 197.1 45 25 90 23 183
#> 16.47 12.63 9.97 14.34 12.52 21.33 21.83 21.60 17.42 6.32 20.94 16.92 9.24
#> 194 113 41 16 145 99 61 113.1 25.1 70 99.1 14.1 69
#> 22.40 22.86 18.02 8.71 10.07 21.19 10.12 22.86 6.32 7.38 21.19 12.89 23.23
#> 136.1 150.1 45.1 187 77 106.1 55 187.1 187.2 106.2 188 13.1 188.1
#> 21.83 20.33 17.42 9.92 7.27 16.67 19.34 9.92 9.92 16.67 16.16 14.34 16.16
#> 188.2 130.1 123.1 32.1 170 99.2 97 181.1 39 23.1 99.3 70.1 88
#> 16.16 16.47 13.00 20.90 19.54 21.19 19.14 16.46 15.59 16.92 21.19 7.38 18.37
#> 13.2 190 78 88.1 149.1 92 76 111 76.1 70.2 184 90.1 61.1
#> 14.34 20.81 23.88 18.37 8.37 22.92 19.22 17.45 19.22 7.38 17.77 20.94 10.12
#> 57 6 106.3 110 183.1 159 128 167.1 145.1 43 46 178 146
#> 14.46 15.64 16.67 17.56 9.24 10.55 20.35 15.55 10.07 12.10 24.00 24.00 24.00
#> 44 46.1 102 21 95 12 152 3 152.1 162 198 144 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 9 82 173 9.1 122 28 161 103 173.1 46.2 142 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28.1 173.2 198.1 7.1 151 19 143 64 20 160 31 182 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 3.1 48 174 119 122.1 144.1 143.1 53 47 193 35 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44.1 120 1 9.2 83 178.1 141.1 137 11 172 21.1 112 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 152.2 95.1 2.1 132 64.1 19.1 109 151.1 22 161.1 104 9.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174.1 185 131 120.1
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[47]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01468865 0.83277564 0.35072340
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.6475174 -0.0141484 -0.2016605
#> grade_iii, Cure model
#> 0.8345361
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 195 11.76 1 NA 1 0
#> 134 17.81 1 47 1 0
#> 189 10.51 1 NA 1 0
#> 124 9.73 1 NA 1 0
#> 108 18.29 1 39 0 1
#> 24 23.89 1 38 0 0
#> 32 20.90 1 37 1 0
#> 183 9.24 1 67 1 0
#> 14 12.89 1 21 0 0
#> 59 10.16 1 NA 1 0
#> 68 20.62 1 44 0 0
#> 136 21.83 1 43 0 1
#> 5 16.43 1 51 0 1
#> 52 10.42 1 52 0 1
#> 166 19.98 1 48 0 0
#> 192 16.44 1 31 1 0
#> 154 12.63 1 20 1 0
#> 177 12.53 1 75 0 0
#> 99 21.19 1 38 0 1
#> 110 17.56 1 65 0 1
#> 45 17.42 1 54 0 1
#> 154.1 12.63 1 20 1 0
#> 188 16.16 1 46 0 1
#> 153 21.33 1 55 1 0
#> 175 21.91 1 43 0 0
#> 188.1 16.16 1 46 0 1
#> 133 14.65 1 57 0 0
#> 24.1 23.89 1 38 0 0
#> 171 16.57 1 41 0 1
#> 195.1 11.76 1 NA 1 0
#> 149 8.37 1 33 1 0
#> 26 15.77 1 49 0 1
#> 37 12.52 1 57 1 0
#> 139 21.49 1 63 1 0
#> 157 15.10 1 47 0 0
#> 61 10.12 1 36 0 1
#> 56 12.21 1 60 0 0
#> 69 23.23 1 25 0 1
#> 170 19.54 1 43 0 1
#> 101 9.97 1 10 0 1
#> 166.1 19.98 1 48 0 0
#> 23 16.92 1 61 0 0
#> 154.2 12.63 1 20 1 0
#> 50 10.02 1 NA 1 0
#> 149.1 8.37 1 33 1 0
#> 25 6.32 1 34 1 0
#> 177.1 12.53 1 75 0 0
#> 194 22.40 1 38 0 1
#> 113 22.86 1 34 0 0
#> 113.1 22.86 1 34 0 0
#> 76 19.22 1 54 0 1
#> 25.1 6.32 1 34 1 0
#> 58 19.34 1 39 0 0
#> 155 13.08 1 26 0 0
#> 5.1 16.43 1 51 0 1
#> 99.1 21.19 1 38 0 1
#> 106 16.67 1 49 1 0
#> 136.1 21.83 1 43 0 1
#> 8 18.43 1 32 0 0
#> 170.1 19.54 1 43 0 1
#> 16 8.71 1 71 0 1
#> 105 19.75 1 60 0 0
#> 194.1 22.40 1 38 0 1
#> 58.1 19.34 1 39 0 0
#> 10 10.53 1 34 0 0
#> 8.1 18.43 1 32 0 0
#> 18 15.21 1 49 1 0
#> 133.1 14.65 1 57 0 0
#> 69.1 23.23 1 25 0 1
#> 66 22.13 1 53 0 0
#> 140 12.68 1 59 1 0
#> 93 10.33 1 52 0 1
#> 106.1 16.67 1 49 1 0
#> 184 17.77 1 38 0 0
#> 114 13.68 1 NA 0 0
#> 154.3 12.63 1 20 1 0
#> 171.1 16.57 1 41 0 1
#> 63 22.77 1 31 1 0
#> 167 15.55 1 56 1 0
#> 194.2 22.40 1 38 0 1
#> 55 19.34 1 69 0 1
#> 168 23.72 1 70 0 0
#> 150 20.33 1 48 0 0
#> 79 16.23 1 54 1 0
#> 153.1 21.33 1 55 1 0
#> 24.2 23.89 1 38 0 0
#> 189.1 10.51 1 NA 1 0
#> 128 20.35 1 35 0 1
#> 195.2 11.76 1 NA 1 0
#> 5.2 16.43 1 51 0 1
#> 56.1 12.21 1 60 0 0
#> 69.2 23.23 1 25 0 1
#> 192.1 16.44 1 31 1 0
#> 30 17.43 1 78 0 0
#> 150.1 20.33 1 48 0 0
#> 159 10.55 1 50 0 1
#> 93.1 10.33 1 52 0 1
#> 158 20.14 1 74 1 0
#> 51 18.23 1 83 0 1
#> 45.1 17.42 1 54 0 1
#> 49 12.19 1 48 1 0
#> 194.3 22.40 1 38 0 1
#> 136.2 21.83 1 43 0 1
#> 128.1 20.35 1 35 0 1
#> 150.2 20.33 1 48 0 0
#> 136.3 21.83 1 43 0 1
#> 61.1 10.12 1 36 0 1
#> 42 12.43 1 49 0 1
#> 37.1 12.52 1 57 1 0
#> 128.2 20.35 1 35 0 1
#> 13 14.34 1 54 0 1
#> 114.1 13.68 1 NA 0 0
#> 11 24.00 0 42 0 1
#> 48 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 178 24.00 0 52 1 0
#> 62 24.00 0 71 0 0
#> 156 24.00 0 50 1 0
#> 12 24.00 0 63 0 0
#> 98 24.00 0 34 1 0
#> 176 24.00 0 43 0 1
#> 67 24.00 0 25 0 0
#> 82 24.00 0 34 0 0
#> 178.1 24.00 0 52 1 0
#> 156.1 24.00 0 50 1 0
#> 19 24.00 0 57 0 1
#> 62.1 24.00 0 71 0 0
#> 147 24.00 0 76 1 0
#> 33 24.00 0 53 0 0
#> 191 24.00 0 60 0 1
#> 17 24.00 0 38 0 1
#> 7 24.00 0 37 1 0
#> 146 24.00 0 63 1 0
#> 118 24.00 0 44 1 0
#> 75 24.00 0 21 1 0
#> 1 24.00 0 23 1 0
#> 120 24.00 0 68 0 1
#> 146.1 24.00 0 63 1 0
#> 62.2 24.00 0 71 0 0
#> 115 24.00 0 NA 1 0
#> 143 24.00 0 51 0 0
#> 144 24.00 0 28 0 1
#> 148 24.00 0 61 1 0
#> 12.1 24.00 0 63 0 0
#> 162 24.00 0 51 0 0
#> 53 24.00 0 32 0 1
#> 185 24.00 0 44 1 0
#> 62.3 24.00 0 71 0 0
#> 182 24.00 0 35 0 0
#> 116 24.00 0 58 0 1
#> 109 24.00 0 48 0 0
#> 120.1 24.00 0 68 0 1
#> 173 24.00 0 19 0 1
#> 62.4 24.00 0 71 0 0
#> 142 24.00 0 53 0 0
#> 80 24.00 0 41 0 0
#> 21 24.00 0 47 0 0
#> 163 24.00 0 66 0 0
#> 47 24.00 0 38 0 1
#> 82.1 24.00 0 34 0 0
#> 2 24.00 0 9 0 0
#> 34 24.00 0 36 0 0
#> 104 24.00 0 50 1 0
#> 27 24.00 0 63 1 0
#> 75.1 24.00 0 21 1 0
#> 54 24.00 0 53 1 0
#> 120.2 24.00 0 68 0 1
#> 151 24.00 0 42 0 0
#> 28 24.00 0 67 1 0
#> 73 24.00 0 NA 0 1
#> 148.1 24.00 0 61 1 0
#> 7.1 24.00 0 37 1 0
#> 118.1 24.00 0 44 1 0
#> 131 24.00 0 66 0 0
#> 160 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#> 143.1 24.00 0 51 0 0
#> 162.1 24.00 0 51 0 0
#> 95.1 24.00 0 68 0 1
#> 17.1 24.00 0 38 0 1
#> 46 24.00 0 71 0 0
#> 38 24.00 0 31 1 0
#> 19.1 24.00 0 57 0 1
#> 147.1 24.00 0 76 1 0
#> 176.1 24.00 0 43 0 1
#> 196 24.00 0 19 0 0
#> 186 24.00 0 45 1 0
#> 156.2 24.00 0 50 1 0
#> 121 24.00 0 57 1 0
#> 138 24.00 0 44 1 0
#> 87 24.00 0 27 0 0
#> 87.1 24.00 0 27 0 0
#> 121.1 24.00 0 57 1 0
#> 83 24.00 0 6 0 0
#> 126 24.00 0 48 0 0
#> 38.1 24.00 0 31 1 0
#> 112 24.00 0 61 0 0
#> 112.1 24.00 0 61 0 0
#> 73.1 24.00 0 NA 0 1
#> 95.2 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.648 NA NA NA
#> 2 age, Cure model -0.0141 NA NA NA
#> 3 grade_ii, Cure model -0.202 NA NA NA
#> 4 grade_iii, Cure model 0.835 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0147 NA NA NA
#> 2 grade_ii, Survival model 0.833 NA NA NA
#> 3 grade_iii, Survival model 0.351 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.64752 -0.01415 -0.20166 0.83454
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.7
#> Residual Deviance: 247.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.6475174 -0.0141484 -0.2016605 0.8345361
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01468865 0.83277564 0.35072340
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.7657084 0.7533804 0.1461859 0.6086192 0.9801001 0.8978628 0.6172740
#> [8] 0.5139898 0.8355215 0.9590830 0.6801604 0.8257180 0.9061654 0.9218975
#> [15] 0.5906831 0.7774771 0.7888895 0.9061654 0.8543275 0.5719023 0.4995511
#> [22] 0.8543275 0.8809650 0.1461859 0.8155990 0.9868873 0.8634098 0.9296637
#> [29] 0.5609214 0.8766571 0.9696756 0.9408868 0.2934001 0.7013953 0.9766264
#> [36] 0.6801604 0.7998373 0.9061654 0.9868873 0.9935040 0.9218975 0.4261212
#> [43] 0.3624794 0.3624794 0.7343502 0.9935040 0.7149423 0.8936617 0.8355215
#> [50] 0.5906831 0.8052759 0.5139898 0.7407555 0.7013953 0.9835115 0.6943607
#> [57] 0.4261212 0.7149423 0.9554847 0.7407555 0.8723280 0.8809650 0.2934001
#> [64] 0.4847353 0.9020568 0.9626537 0.8052759 0.7716095 0.9061654 0.8155990
#> [71] 0.4064066 0.8679174 0.4261212 0.7149423 0.2590796 0.6497787 0.8496855
#> [78] 0.5719023 0.1461859 0.6258200 0.8355215 0.9408868 0.2934001 0.8257180
#> [85] 0.7832279 0.6497787 0.9518777 0.9626537 0.6728660 0.7596396 0.7888895
#> [92] 0.9482437 0.4261212 0.5139898 0.6258200 0.6497787 0.5139898 0.9696756
#> [99] 0.9371598 0.9296637 0.6258200 0.8894514 0.0000000 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 134 108 24 32 183 14 68 136 5 52 166 192 154
#> 17.81 18.29 23.89 20.90 9.24 12.89 20.62 21.83 16.43 10.42 19.98 16.44 12.63
#> 177 99 110 45 154.1 188 153 175 188.1 133 24.1 171 149
#> 12.53 21.19 17.56 17.42 12.63 16.16 21.33 21.91 16.16 14.65 23.89 16.57 8.37
#> 26 37 139 157 61 56 69 170 101 166.1 23 154.2 149.1
#> 15.77 12.52 21.49 15.10 10.12 12.21 23.23 19.54 9.97 19.98 16.92 12.63 8.37
#> 25 177.1 194 113 113.1 76 25.1 58 155 5.1 99.1 106 136.1
#> 6.32 12.53 22.40 22.86 22.86 19.22 6.32 19.34 13.08 16.43 21.19 16.67 21.83
#> 8 170.1 16 105 194.1 58.1 10 8.1 18 133.1 69.1 66 140
#> 18.43 19.54 8.71 19.75 22.40 19.34 10.53 18.43 15.21 14.65 23.23 22.13 12.68
#> 93 106.1 184 154.3 171.1 63 167 194.2 55 168 150 79 153.1
#> 10.33 16.67 17.77 12.63 16.57 22.77 15.55 22.40 19.34 23.72 20.33 16.23 21.33
#> 24.2 128 5.2 56.1 69.2 192.1 30 150.1 159 93.1 158 51 45.1
#> 23.89 20.35 16.43 12.21 23.23 16.44 17.43 20.33 10.55 10.33 20.14 18.23 17.42
#> 49 194.3 136.2 128.1 150.2 136.3 61.1 42 37.1 128.2 13 11 48
#> 12.19 22.40 21.83 20.35 20.33 21.83 10.12 12.43 12.52 20.35 14.34 24.00 24.00
#> 174 178 62 156 12 98 176 67 82 178.1 156.1 19 62.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 33 191 17 7 146 118 75 1 120 146.1 62.2 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 148 12.1 162 53 185 62.3 182 116 109 120.1 173 62.4
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 80 21 163 47 82.1 2 34 104 27 75.1 54 120.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151 28 148.1 7.1 118.1 131 160 95 143.1 162.1 95.1 17.1 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 19.1 147.1 176.1 196 186 156.2 121 138 87 87.1 121.1 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 38.1 112 112.1 95.2
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[48]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.005799595 0.837204712 0.602348200
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.051976070 -0.008767838 0.372485798
#> grade_iii, Cure model
#> 1.173781856
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 180 14.82 1 37 0 0
#> 14 12.89 1 21 0 0
#> 36 21.19 1 48 0 1
#> 5 16.43 1 51 0 1
#> 154 12.63 1 20 1 0
#> 77 7.27 1 67 0 1
#> 60 13.15 1 38 1 0
#> 175 21.91 1 43 0 0
#> 113 22.86 1 34 0 0
#> 89 11.44 1 NA 0 0
#> 32 20.90 1 37 1 0
#> 149 8.37 1 33 1 0
#> 197 21.60 1 69 1 0
#> 45 17.42 1 54 0 1
#> 78 23.88 1 43 0 0
#> 79 16.23 1 54 1 0
#> 63 22.77 1 31 1 0
#> 114 13.68 1 NA 0 0
#> 183 9.24 1 67 1 0
#> 108 18.29 1 39 0 1
#> 45.1 17.42 1 54 0 1
#> 150 20.33 1 48 0 0
#> 45.2 17.42 1 54 0 1
#> 57 14.46 1 45 0 1
#> 100 16.07 1 60 0 0
#> 175.1 21.91 1 43 0 0
#> 36.1 21.19 1 48 0 1
#> 101 9.97 1 10 0 1
#> 145 10.07 1 65 1 0
#> 5.1 16.43 1 51 0 1
#> 78.1 23.88 1 43 0 0
#> 199 19.81 1 NA 0 1
#> 13 14.34 1 54 0 1
#> 51 18.23 1 83 0 1
#> 43 12.10 1 61 0 1
#> 90 20.94 1 50 0 1
#> 106 16.67 1 49 1 0
#> 39 15.59 1 37 0 1
#> 124 9.73 1 NA 1 0
#> 10 10.53 1 34 0 0
#> 78.2 23.88 1 43 0 0
#> 90.1 20.94 1 50 0 1
#> 56 12.21 1 60 0 0
#> 195 11.76 1 NA 1 0
#> 39.1 15.59 1 37 0 1
#> 59 10.16 1 NA 1 0
#> 63.1 22.77 1 31 1 0
#> 190 20.81 1 42 1 0
#> 110 17.56 1 65 0 1
#> 92 22.92 1 47 0 1
#> 170 19.54 1 43 0 1
#> 155 13.08 1 26 0 0
#> 150.1 20.33 1 48 0 0
#> 117 17.46 1 26 0 1
#> 117.1 17.46 1 26 0 1
#> 136 21.83 1 43 0 1
#> 56.1 12.21 1 60 0 0
#> 145.1 10.07 1 65 1 0
#> 32.1 20.90 1 37 1 0
#> 108.1 18.29 1 39 0 1
#> 15 22.68 1 48 0 0
#> 106.1 16.67 1 49 1 0
#> 110.1 17.56 1 65 0 1
#> 190.1 20.81 1 42 1 0
#> 108.2 18.29 1 39 0 1
#> 101.1 9.97 1 10 0 1
#> 93 10.33 1 52 0 1
#> 92.1 22.92 1 47 0 1
#> 150.2 20.33 1 48 0 0
#> 188 16.16 1 46 0 1
#> 110.2 17.56 1 65 0 1
#> 59.1 10.16 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 93.1 10.33 1 52 0 1
#> 188.1 16.16 1 46 0 1
#> 51.1 18.23 1 83 0 1
#> 29 15.45 1 68 1 0
#> 100.1 16.07 1 60 0 0
#> 153 21.33 1 55 1 0
#> 192 16.44 1 31 1 0
#> 49 12.19 1 48 1 0
#> 113.1 22.86 1 34 0 0
#> 25 6.32 1 34 1 0
#> 70 7.38 1 30 1 0
#> 175.2 21.91 1 43 0 0
#> 170.1 19.54 1 43 0 1
#> 133 14.65 1 57 0 0
#> 91 5.33 1 61 0 1
#> 128 20.35 1 35 0 1
#> 39.2 15.59 1 37 0 1
#> 99 21.19 1 38 0 1
#> 188.2 16.16 1 46 0 1
#> 150.3 20.33 1 48 0 0
#> 166 19.98 1 48 0 0
#> 15.1 22.68 1 48 0 0
#> 60.1 13.15 1 38 1 0
#> 197.1 21.60 1 69 1 0
#> 114.1 13.68 1 NA 0 0
#> 92.2 22.92 1 47 0 1
#> 199.1 19.81 1 NA 0 1
#> 105 19.75 1 60 0 0
#> 90.2 20.94 1 50 0 1
#> 36.2 21.19 1 48 0 1
#> 29.1 15.45 1 68 1 0
#> 41 18.02 1 40 1 0
#> 25.1 6.32 1 34 1 0
#> 187 9.92 1 39 1 0
#> 117.2 17.46 1 26 0 1
#> 107 11.18 1 54 1 0
#> 169 22.41 1 46 0 0
#> 16 8.71 1 71 0 1
#> 114.2 13.68 1 NA 0 0
#> 95 24.00 0 68 0 1
#> 172 24.00 0 41 0 0
#> 120 24.00 0 68 0 1
#> 182 24.00 0 35 0 0
#> 200 24.00 0 64 0 0
#> 64 24.00 0 43 0 0
#> 48 24.00 0 31 1 0
#> 120.1 24.00 0 68 0 1
#> 28 24.00 0 67 1 0
#> 54 24.00 0 53 1 0
#> 62 24.00 0 71 0 0
#> 38 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 95.1 24.00 0 68 0 1
#> 54.1 24.00 0 53 1 0
#> 141 24.00 0 44 1 0
#> 53 24.00 0 32 0 1
#> 193 24.00 0 45 0 1
#> 152 24.00 0 36 0 1
#> 148 24.00 0 61 1 0
#> 71 24.00 0 51 0 0
#> 116 24.00 0 58 0 1
#> 119 24.00 0 17 0 0
#> 122 24.00 0 66 0 0
#> 104 24.00 0 50 1 0
#> 53.1 24.00 0 32 0 1
#> 147 24.00 0 76 1 0
#> 102 24.00 0 49 0 0
#> 144 24.00 0 28 0 1
#> 109 24.00 0 48 0 0
#> 116.1 24.00 0 58 0 1
#> 196 24.00 0 19 0 0
#> 119.1 24.00 0 17 0 0
#> 182.1 24.00 0 35 0 0
#> 33 24.00 0 53 0 0
#> 141.1 24.00 0 44 1 0
#> 119.2 24.00 0 17 0 0
#> 200.1 24.00 0 64 0 0
#> 27 24.00 0 63 1 0
#> 62.1 24.00 0 71 0 0
#> 17 24.00 0 38 0 1
#> 121 24.00 0 57 1 0
#> 34 24.00 0 36 0 0
#> 54.2 24.00 0 53 1 0
#> 174.1 24.00 0 49 1 0
#> 87 24.00 0 27 0 0
#> 196.1 24.00 0 19 0 0
#> 112 24.00 0 61 0 0
#> 98 24.00 0 34 1 0
#> 121.1 24.00 0 57 1 0
#> 122.1 24.00 0 66 0 0
#> 119.3 24.00 0 17 0 0
#> 3 24.00 0 31 1 0
#> 53.2 24.00 0 32 0 1
#> 146 24.00 0 63 1 0
#> 65 24.00 0 57 1 0
#> 191 24.00 0 60 0 1
#> 20 24.00 0 46 1 0
#> 138 24.00 0 44 1 0
#> 142 24.00 0 53 0 0
#> 163 24.00 0 66 0 0
#> 163.1 24.00 0 66 0 0
#> 27.1 24.00 0 63 1 0
#> 126 24.00 0 48 0 0
#> 198 24.00 0 66 0 1
#> 7 24.00 0 37 1 0
#> 147.1 24.00 0 76 1 0
#> 19 24.00 0 57 0 1
#> 162 24.00 0 51 0 0
#> 142.1 24.00 0 53 0 0
#> 126.1 24.00 0 48 0 0
#> 35 24.00 0 51 0 0
#> 80 24.00 0 41 0 0
#> 19.1 24.00 0 57 0 1
#> 173 24.00 0 19 0 1
#> 73 24.00 0 NA 0 1
#> 156 24.00 0 50 1 0
#> 173.1 24.00 0 19 0 1
#> 103 24.00 0 56 1 0
#> 74 24.00 0 43 0 1
#> 162.1 24.00 0 51 0 0
#> 172.1 24.00 0 41 0 0
#> 186 24.00 0 45 1 0
#> 12 24.00 0 63 0 0
#> 12.1 24.00 0 63 0 0
#> 9 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 142.2 24.00 0 53 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.0520 NA NA NA
#> 2 age, Cure model -0.00877 NA NA NA
#> 3 grade_ii, Cure model 0.372 NA NA NA
#> 4 grade_iii, Cure model 1.17 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00580 NA NA NA
#> 2 grade_ii, Survival model 0.837 NA NA NA
#> 3 grade_iii, Survival model 0.602 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.051976 -0.008768 0.372486 1.173782
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 249.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.051976070 -0.008767838 0.372485798 1.173781856
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.005799595 0.837204712 0.602348200
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.85799965 0.89378765 0.48144211 0.78646632 0.89880014 0.98290230
#> [7] 0.87875840 0.38360015 0.25985743 0.55135045 0.97412785 0.44399177
#> [13] 0.74351341 0.09085413 0.79807703 0.30141310 0.96521083 0.65976788
#> [19] 0.74351341 0.59501918 0.74351341 0.86845065 0.82041073 0.38360015
#> [25] 0.48144211 0.95156976 0.94237335 0.78646632 0.09085413 0.87362730
#> [31] 0.68225885 0.91852401 0.52262131 0.76230803 0.83145120 0.92816936
#> [37] 0.09085413 0.52262131 0.90376846 0.83145120 0.30141310 0.56948950
#> [43] 0.70383414 0.19805347 0.64398966 0.88877152 0.59501918 0.72397912
#> [49] 0.72397912 0.42902011 0.90376846 0.94237335 0.55135045 0.65976788
#> [55] 0.33484954 0.76230803 0.70383414 0.56948950 0.65976788 0.95156976
#> [61] 0.93295944 0.19805347 0.59501918 0.80381321 0.70383414 0.77447437
#> [67] 0.93295944 0.80381321 0.68225885 0.84755295 0.82041073 0.46932293
#> [73] 0.78051099 0.91363278 0.25985743 0.98723966 0.97853227 0.38360015
#> [79] 0.64398966 0.86323135 0.99575986 0.58656946 0.83145120 0.48144211
#> [85] 0.80381321 0.59501918 0.62752533 0.33484954 0.87875840 0.44399177
#> [91] 0.19805347 0.63577967 0.52262131 0.48144211 0.84755295 0.69671183
#> [97] 0.98723966 0.96068378 0.72397912 0.92337388 0.36725090 0.96968735
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 180 14 36 5 154 77 60 175 113 32 149 197 45
#> 14.82 12.89 21.19 16.43 12.63 7.27 13.15 21.91 22.86 20.90 8.37 21.60 17.42
#> 78 79 63 183 108 45.1 150 45.2 57 100 175.1 36.1 101
#> 23.88 16.23 22.77 9.24 18.29 17.42 20.33 17.42 14.46 16.07 21.91 21.19 9.97
#> 145 5.1 78.1 13 51 43 90 106 39 10 78.2 90.1 56
#> 10.07 16.43 23.88 14.34 18.23 12.10 20.94 16.67 15.59 10.53 23.88 20.94 12.21
#> 39.1 63.1 190 110 92 170 155 150.1 117 117.1 136 56.1 145.1
#> 15.59 22.77 20.81 17.56 22.92 19.54 13.08 20.33 17.46 17.46 21.83 12.21 10.07
#> 32.1 108.1 15 106.1 110.1 190.1 108.2 101.1 93 92.1 150.2 188 110.2
#> 20.90 18.29 22.68 16.67 17.56 20.81 18.29 9.97 10.33 22.92 20.33 16.16 17.56
#> 130 93.1 188.1 51.1 29 100.1 153 192 49 113.1 25 70 175.2
#> 16.47 10.33 16.16 18.23 15.45 16.07 21.33 16.44 12.19 22.86 6.32 7.38 21.91
#> 170.1 133 91 128 39.2 99 188.2 150.3 166 15.1 60.1 197.1 92.2
#> 19.54 14.65 5.33 20.35 15.59 21.19 16.16 20.33 19.98 22.68 13.15 21.60 22.92
#> 105 90.2 36.2 29.1 41 25.1 187 117.2 107 169 16 95 172
#> 19.75 20.94 21.19 15.45 18.02 6.32 9.92 17.46 11.18 22.41 8.71 24.00 24.00
#> 120 182 200 64 48 120.1 28 54 62 38 174 95.1 54.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 53 193 152 148 71 116 119 122 104 53.1 147 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 109 116.1 196 119.1 182.1 33 141.1 119.2 200.1 27 62.1 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 34 54.2 174.1 87 196.1 112 98 121.1 122.1 119.3 3 53.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 65 191 20 138 142 163 163.1 27.1 126 198 7 147.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 162 142.1 126.1 35 80 19.1 173 156 173.1 103 74 162.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.1 186 12 12.1 9 47 142.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[49]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.002651811 0.413093364 0.272842701
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.37803478 0.01954209 0.40524140
#> grade_iii, Cure model
#> 1.36374724
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 26 15.77 1 49 0 1
#> 25 6.32 1 34 1 0
#> 76 19.22 1 54 0 1
#> 111 17.45 1 47 0 1
#> 45 17.42 1 54 0 1
#> 189 10.51 1 NA 1 0
#> 51 18.23 1 83 0 1
#> 194 22.40 1 38 0 1
#> 180 14.82 1 37 0 0
#> 183 9.24 1 67 1 0
#> 18 15.21 1 49 1 0
#> 170 19.54 1 43 0 1
#> 105 19.75 1 60 0 0
#> 40 18.00 1 28 1 0
#> 60 13.15 1 38 1 0
#> 76.1 19.22 1 54 0 1
#> 57 14.46 1 45 0 1
#> 199 19.81 1 NA 0 1
#> 105.1 19.75 1 60 0 0
#> 170.1 19.54 1 43 0 1
#> 177 12.53 1 75 0 0
#> 108 18.29 1 39 0 1
#> 26.1 15.77 1 49 0 1
#> 51.1 18.23 1 83 0 1
#> 194.1 22.40 1 38 0 1
#> 69 23.23 1 25 0 1
#> 189.1 10.51 1 NA 1 0
#> 180.1 14.82 1 37 0 0
#> 101 9.97 1 10 0 1
#> 15 22.68 1 48 0 0
#> 195 11.76 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 24 23.89 1 38 0 0
#> 79 16.23 1 54 1 0
#> 90 20.94 1 50 0 1
#> 155 13.08 1 26 0 0
#> 25.1 6.32 1 34 1 0
#> 105.2 19.75 1 60 0 0
#> 40.1 18.00 1 28 1 0
#> 99 21.19 1 38 0 1
#> 164 23.60 1 76 0 1
#> 128 20.35 1 35 0 1
#> 41 18.02 1 40 1 0
#> 4 17.64 1 NA 0 1
#> 164.1 23.60 1 76 0 1
#> 24.1 23.89 1 38 0 0
#> 59 10.16 1 NA 1 0
#> 188 16.16 1 46 0 1
#> 189.2 10.51 1 NA 1 0
#> 29 15.45 1 68 1 0
#> 36 21.19 1 48 0 1
#> 25.2 6.32 1 34 1 0
#> 52 10.42 1 52 0 1
#> 16 8.71 1 71 0 1
#> 183.1 9.24 1 67 1 0
#> 127 3.53 1 62 0 1
#> 6 15.64 1 39 0 0
#> 15.1 22.68 1 48 0 0
#> 154 12.63 1 20 1 0
#> 51.2 18.23 1 83 0 1
#> 197 21.60 1 69 1 0
#> 197.1 21.60 1 69 1 0
#> 39 15.59 1 37 0 1
#> 29.1 15.45 1 68 1 0
#> 117 17.46 1 26 0 1
#> 108.1 18.29 1 39 0 1
#> 68 20.62 1 44 0 0
#> 125 15.65 1 67 1 0
#> 76.2 19.22 1 54 0 1
#> 89 11.44 1 NA 0 0
#> 97 19.14 1 65 0 1
#> 97.1 19.14 1 65 0 1
#> 157 15.10 1 47 0 0
#> 177.1 12.53 1 75 0 0
#> 85 16.44 1 36 0 0
#> 111.1 17.45 1 47 0 1
#> 124 9.73 1 NA 1 0
#> 139 21.49 1 63 1 0
#> 195.1 11.76 1 NA 1 0
#> 5 16.43 1 51 0 1
#> 50 10.02 1 NA 1 0
#> 180.2 14.82 1 37 0 0
#> 150 20.33 1 48 0 0
#> 23 16.92 1 61 0 0
#> 197.2 21.60 1 69 1 0
#> 43 12.10 1 61 0 1
#> 127.1 3.53 1 62 0 1
#> 36.1 21.19 1 48 0 1
#> 40.2 18.00 1 28 1 0
#> 107 11.18 1 54 1 0
#> 159 10.55 1 50 0 1
#> 39.1 15.59 1 37 0 1
#> 171 16.57 1 41 0 1
#> 69.1 23.23 1 25 0 1
#> 183.2 9.24 1 67 1 0
#> 91 5.33 1 61 0 1
#> 58 19.34 1 39 0 0
#> 37 12.52 1 57 1 0
#> 108.2 18.29 1 39 0 1
#> 63 22.77 1 31 1 0
#> 92 22.92 1 47 0 1
#> 63.1 22.77 1 31 1 0
#> 63.2 22.77 1 31 1 0
#> 166 19.98 1 48 0 0
#> 5.1 16.43 1 51 0 1
#> 168 23.72 1 70 0 0
#> 100 16.07 1 60 0 0
#> 189.3 10.51 1 NA 1 0
#> 79.1 16.23 1 54 1 0
#> 117.1 17.46 1 26 0 1
#> 129 23.41 1 53 1 0
#> 190 20.81 1 42 1 0
#> 186 24.00 0 45 1 0
#> 120 24.00 0 68 0 1
#> 118 24.00 0 44 1 0
#> 126 24.00 0 48 0 0
#> 3 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 84 24.00 0 39 0 1
#> 74 24.00 0 43 0 1
#> 120.1 24.00 0 68 0 1
#> 33 24.00 0 53 0 0
#> 46 24.00 0 71 0 0
#> 151 24.00 0 42 0 0
#> 53 24.00 0 32 0 1
#> 2 24.00 0 9 0 0
#> 143 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 54 24.00 0 53 1 0
#> 62 24.00 0 71 0 0
#> 33.1 24.00 0 53 0 0
#> 20 24.00 0 46 1 0
#> 3.1 24.00 0 31 1 0
#> 103 24.00 0 56 1 0
#> 35 24.00 0 51 0 0
#> 28 24.00 0 67 1 0
#> 196 24.00 0 19 0 0
#> 33.2 24.00 0 53 0 0
#> 151.1 24.00 0 42 0 0
#> 121 24.00 0 57 1 0
#> 131 24.00 0 66 0 0
#> 161 24.00 0 45 0 0
#> 75 24.00 0 21 1 0
#> 174 24.00 0 49 1 0
#> 74.1 24.00 0 43 0 1
#> 160 24.00 0 31 1 0
#> 162 24.00 0 51 0 0
#> 83 24.00 0 6 0 0
#> 20.1 24.00 0 46 1 0
#> 193 24.00 0 45 0 1
#> 116 24.00 0 58 0 1
#> 119 24.00 0 17 0 0
#> 73 24.00 0 NA 0 1
#> 160.1 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 200 24.00 0 64 0 0
#> 31 24.00 0 36 0 1
#> 1 24.00 0 23 1 0
#> 48 24.00 0 31 1 0
#> 112 24.00 0 61 0 0
#> 156 24.00 0 50 1 0
#> 120.2 24.00 0 68 0 1
#> 74.2 24.00 0 43 0 1
#> 104.1 24.00 0 50 1 0
#> 53.1 24.00 0 32 0 1
#> 163 24.00 0 66 0 0
#> 22 24.00 0 52 1 0
#> 151.2 24.00 0 42 0 0
#> 112.1 24.00 0 61 0 0
#> 112.2 24.00 0 61 0 0
#> 98 24.00 0 34 1 0
#> 28.1 24.00 0 67 1 0
#> 11 24.00 0 42 0 1
#> 146 24.00 0 63 1 0
#> 172 24.00 0 41 0 0
#> 186.1 24.00 0 45 1 0
#> 34 24.00 0 36 0 0
#> 161.1 24.00 0 45 0 0
#> 176 24.00 0 43 0 1
#> 141 24.00 0 44 1 0
#> 165 24.00 0 47 0 0
#> 62.1 24.00 0 71 0 0
#> 120.3 24.00 0 68 0 1
#> 144 24.00 0 28 0 1
#> 74.3 24.00 0 43 0 1
#> 98.1 24.00 0 34 1 0
#> 53.2 24.00 0 32 0 1
#> 75.1 24.00 0 21 1 0
#> 156.1 24.00 0 50 1 0
#> 119.1 24.00 0 17 0 0
#> 138 24.00 0 44 1 0
#> 112.3 24.00 0 61 0 0
#> 80 24.00 0 41 0 0
#> 148 24.00 0 61 1 0
#> 173 24.00 0 19 0 1
#> 122 24.00 0 66 0 0
#> 64 24.00 0 43 0 0
#> 196.1 24.00 0 19 0 0
#> 64.1 24.00 0 43 0 0
#> 67 24.00 0 25 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.38 NA NA NA
#> 2 age, Cure model 0.0195 NA NA NA
#> 3 grade_ii, Cure model 0.405 NA NA NA
#> 4 grade_iii, Cure model 1.36 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00265 NA NA NA
#> 2 grade_ii, Survival model 0.413 NA NA NA
#> 3 grade_iii, Survival model 0.273 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.37803 0.01954 0.40524 1.36375
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258.3
#> Residual Deviance: 240.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.37803478 0.01954209 0.40524140 1.36374724
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.002651811 0.413093364 0.272842701
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.74744721 0.95945554 0.49360476 0.64292478 0.66757263 0.56662332
#> [7] 0.27262874 0.82315132 0.93185419 0.80827817 0.46445574 0.43511782
#> [13] 0.60127143 0.85256448 0.49360476 0.84518591 0.43511782 0.46445574
#> [19] 0.87452670 0.53988873 0.74744721 0.56662332 0.27262874 0.16060380
#> [25] 0.82315132 0.92478003 0.24651038 0.65933800 0.03184636 0.71609345
#> [31] 0.37344362 0.85990040 0.95945554 0.43511782 0.60127143 0.34228487
#> [37] 0.10540436 0.40463430 0.59257805 0.10540436 0.03184636 0.73177593
#> [43] 0.79336597 0.34228487 0.95945554 0.91768693 0.95253946 0.93185419
#> [49] 0.98656217 0.77054721 0.24651038 0.86723186 0.56662332 0.29766329
#> [55] 0.29766329 0.77822320 0.79336597 0.62630451 0.53988873 0.39432494
#> [61] 0.76286288 0.49360476 0.52149587 0.52149587 0.81571924 0.87452670
#> [67] 0.69204054 0.64292478 0.33106226 0.70015117 0.82315132 0.41482901
#> [73] 0.67575519 0.29766329 0.89622552 0.98656217 0.34228487 0.60127143
#> [79] 0.90341688 0.91056588 0.77822320 0.68392038 0.16060380 0.93185419
#> [85] 0.97976931 0.48383675 0.88900262 0.53988873 0.20785371 0.19207344
#> [91] 0.20785371 0.20785371 0.42498984 0.70015117 0.07865453 0.73961873
#> [97] 0.71609345 0.62630451 0.14251693 0.38398214 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 26 25 76 111 45 51 194 180 183 18 170 105 40
#> 15.77 6.32 19.22 17.45 17.42 18.23 22.40 14.82 9.24 15.21 19.54 19.75 18.00
#> 60 76.1 57 105.1 170.1 177 108 26.1 51.1 194.1 69 180.1 101
#> 13.15 19.22 14.46 19.75 19.54 12.53 18.29 15.77 18.23 22.40 23.23 14.82 9.97
#> 15 30 24 79 90 155 25.1 105.2 40.1 99 164 128 41
#> 22.68 17.43 23.89 16.23 20.94 13.08 6.32 19.75 18.00 21.19 23.60 20.35 18.02
#> 164.1 24.1 188 29 36 25.2 52 16 183.1 127 6 15.1 154
#> 23.60 23.89 16.16 15.45 21.19 6.32 10.42 8.71 9.24 3.53 15.64 22.68 12.63
#> 51.2 197 197.1 39 29.1 117 108.1 68 125 76.2 97 97.1 157
#> 18.23 21.60 21.60 15.59 15.45 17.46 18.29 20.62 15.65 19.22 19.14 19.14 15.10
#> 177.1 85 111.1 139 5 180.2 150 23 197.2 43 127.1 36.1 40.2
#> 12.53 16.44 17.45 21.49 16.43 14.82 20.33 16.92 21.60 12.10 3.53 21.19 18.00
#> 107 159 39.1 171 69.1 183.2 91 58 37 108.2 63 92 63.1
#> 11.18 10.55 15.59 16.57 23.23 9.24 5.33 19.34 12.52 18.29 22.77 22.92 22.77
#> 63.2 166 5.1 168 100 79.1 117.1 129 190 186 120 118 126
#> 22.77 19.98 16.43 23.72 16.07 16.23 17.46 23.41 20.81 24.00 24.00 24.00 24.00
#> 3 7 84 74 120.1 33 46 151 53 2 143 21 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 33.1 20 3.1 103 35 28 196 33.2 151.1 121 131 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 174 74.1 160 162 83 20.1 193 116 119 160.1 104 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 1 48 112 156 120.2 74.2 104.1 53.1 163 22 151.2 112.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112.2 98 28.1 11 146 172 186.1 34 161.1 176 141 165 62.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120.3 144 74.3 98.1 53.2 75.1 156.1 119.1 138 112.3 80 148 173
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 64 196.1 64.1 67
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[50]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01621068 0.42053521 0.32330140
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.64161367 -0.01692827 0.06958740
#> grade_iii, Cure model
#> 1.00441582
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 96 14.54 1 33 0 1
#> 155 13.08 1 26 0 0
#> 90 20.94 1 50 0 1
#> 68 20.62 1 44 0 0
#> 36 21.19 1 48 0 1
#> 130 16.47 1 53 0 1
#> 52 10.42 1 52 0 1
#> 108 18.29 1 39 0 1
#> 99 21.19 1 38 0 1
#> 66 22.13 1 53 0 0
#> 153 21.33 1 55 1 0
#> 76 19.22 1 54 0 1
#> 188 16.16 1 46 0 1
#> 81 14.06 1 34 0 0
#> 149 8.37 1 33 1 0
#> 124 9.73 1 NA 1 0
#> 149.1 8.37 1 33 1 0
#> 23 16.92 1 61 0 0
#> 149.2 8.37 1 33 1 0
#> 59 10.16 1 NA 1 0
#> 45 17.42 1 54 0 1
#> 158 20.14 1 74 1 0
#> 175 21.91 1 43 0 0
#> 192 16.44 1 31 1 0
#> 130.1 16.47 1 53 0 1
#> 150 20.33 1 48 0 0
#> 45.1 17.42 1 54 0 1
#> 145 10.07 1 65 1 0
#> 8 18.43 1 32 0 0
#> 171 16.57 1 41 0 1
#> 5 16.43 1 51 0 1
#> 199 19.81 1 NA 0 1
#> 190 20.81 1 42 1 0
#> 190.1 20.81 1 42 1 0
#> 88 18.37 1 47 0 0
#> 41 18.02 1 40 1 0
#> 55 19.34 1 69 0 1
#> 170 19.54 1 43 0 1
#> 168 23.72 1 70 0 0
#> 15 22.68 1 48 0 0
#> 164 23.60 1 76 0 1
#> 155.1 13.08 1 26 0 0
#> 63 22.77 1 31 1 0
#> 107 11.18 1 54 1 0
#> 50 10.02 1 NA 1 0
#> 5.1 16.43 1 51 0 1
#> 60 13.15 1 38 1 0
#> 58 19.34 1 39 0 0
#> 58.1 19.34 1 39 0 0
#> 111 17.45 1 47 0 1
#> 68.1 20.62 1 44 0 0
#> 30 17.43 1 78 0 0
#> 63.1 22.77 1 31 1 0
#> 60.1 13.15 1 38 1 0
#> 25 6.32 1 34 1 0
#> 93 10.33 1 52 0 1
#> 130.2 16.47 1 53 0 1
#> 158.1 20.14 1 74 1 0
#> 58.2 19.34 1 39 0 0
#> 123 13.00 1 44 1 0
#> 91 5.33 1 61 0 1
#> 79 16.23 1 54 1 0
#> 170.1 19.54 1 43 0 1
#> 179 18.63 1 42 0 0
#> 16 8.71 1 71 0 1
#> 180 14.82 1 37 0 0
#> 52.1 10.42 1 52 0 1
#> 128 20.35 1 35 0 1
#> 13 14.34 1 54 0 1
#> 117 17.46 1 26 0 1
#> 133 14.65 1 57 0 0
#> 108.1 18.29 1 39 0 1
#> 124.1 9.73 1 NA 1 0
#> 149.3 8.37 1 33 1 0
#> 45.2 17.42 1 54 0 1
#> 117.1 17.46 1 26 0 1
#> 97 19.14 1 65 0 1
#> 188.1 16.16 1 46 0 1
#> 25.1 6.32 1 34 1 0
#> 106 16.67 1 49 1 0
#> 140 12.68 1 59 1 0
#> 49 12.19 1 48 1 0
#> 14 12.89 1 21 0 0
#> 195 11.76 1 NA 1 0
#> 134 17.81 1 47 1 0
#> 166 19.98 1 48 0 0
#> 92 22.92 1 47 0 1
#> 101 9.97 1 10 0 1
#> 155.2 13.08 1 26 0 0
#> 23.1 16.92 1 61 0 0
#> 99.1 21.19 1 38 0 1
#> 179.1 18.63 1 42 0 0
#> 52.2 10.42 1 52 0 1
#> 199.1 19.81 1 NA 0 1
#> 58.3 19.34 1 39 0 0
#> 16.1 8.71 1 71 0 1
#> 129 23.41 1 53 1 0
#> 43 12.10 1 61 0 1
#> 78 23.88 1 43 0 0
#> 139 21.49 1 63 1 0
#> 81.1 14.06 1 34 0 0
#> 140.1 12.68 1 59 1 0
#> 85 16.44 1 36 0 0
#> 195.1 11.76 1 NA 1 0
#> 86 23.81 1 58 0 1
#> 55.1 19.34 1 69 0 1
#> 55.2 19.34 1 69 0 1
#> 52.3 10.42 1 52 0 1
#> 81.2 14.06 1 34 0 0
#> 114 13.68 1 NA 0 0
#> 187 9.92 1 39 1 0
#> 70 7.38 1 30 1 0
#> 191 24.00 0 60 0 1
#> 35 24.00 0 51 0 0
#> 172 24.00 0 41 0 0
#> 2 24.00 0 9 0 0
#> 138 24.00 0 44 1 0
#> 74 24.00 0 43 0 1
#> 132 24.00 0 55 0 0
#> 83 24.00 0 6 0 0
#> 185 24.00 0 44 1 0
#> 191.1 24.00 0 60 0 1
#> 75 24.00 0 21 1 0
#> 28 24.00 0 67 1 0
#> 7 24.00 0 37 1 0
#> 83.1 24.00 0 6 0 0
#> 120 24.00 0 68 0 1
#> 148 24.00 0 61 1 0
#> 156 24.00 0 50 1 0
#> 161 24.00 0 45 0 0
#> 65 24.00 0 57 1 0
#> 137 24.00 0 45 1 0
#> 48 24.00 0 31 1 0
#> 102 24.00 0 49 0 0
#> 182 24.00 0 35 0 0
#> 185.1 24.00 0 44 1 0
#> 182.1 24.00 0 35 0 0
#> 165 24.00 0 47 0 0
#> 120.1 24.00 0 68 0 1
#> 121 24.00 0 57 1 0
#> 178 24.00 0 52 1 0
#> 72 24.00 0 40 0 1
#> 48.1 24.00 0 31 1 0
#> 20 24.00 0 46 1 0
#> 1 24.00 0 23 1 0
#> 80 24.00 0 41 0 0
#> 21 24.00 0 47 0 0
#> 103 24.00 0 56 1 0
#> 193 24.00 0 45 0 1
#> 156.1 24.00 0 50 1 0
#> 98 24.00 0 34 1 0
#> 131 24.00 0 66 0 0
#> 122 24.00 0 66 0 0
#> 126 24.00 0 48 0 0
#> 74.1 24.00 0 43 0 1
#> 67 24.00 0 25 0 0
#> 46 24.00 0 71 0 0
#> 115 24.00 0 NA 1 0
#> 62 24.00 0 71 0 0
#> 178.1 24.00 0 52 1 0
#> 152 24.00 0 36 0 1
#> 119 24.00 0 17 0 0
#> 44 24.00 0 56 0 0
#> 103.1 24.00 0 56 1 0
#> 186 24.00 0 45 1 0
#> 82 24.00 0 34 0 0
#> 74.2 24.00 0 43 0 1
#> 185.2 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 198 24.00 0 66 0 1
#> 115.1 24.00 0 NA 1 0
#> 185.3 24.00 0 44 1 0
#> 160 24.00 0 31 1 0
#> 146 24.00 0 63 1 0
#> 131.1 24.00 0 66 0 0
#> 172.1 24.00 0 41 0 0
#> 191.2 24.00 0 60 0 1
#> 182.2 24.00 0 35 0 0
#> 35.1 24.00 0 51 0 0
#> 12 24.00 0 63 0 0
#> 3 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 191.3 24.00 0 60 0 1
#> 185.4 24.00 0 44 1 0
#> 12.1 24.00 0 63 0 0
#> 191.4 24.00 0 60 0 1
#> 22 24.00 0 52 1 0
#> 94 24.00 0 51 0 1
#> 146.1 24.00 0 63 1 0
#> 98.1 24.00 0 34 1 0
#> 17 24.00 0 38 0 1
#> 132.1 24.00 0 55 0 0
#> 95 24.00 0 68 0 1
#> 198.1 24.00 0 66 0 1
#> 116 24.00 0 58 0 1
#> 147 24.00 0 76 1 0
#> 46.1 24.00 0 71 0 0
#> 35.2 24.00 0 51 0 0
#> 46.2 24.00 0 71 0 0
#> 122.1 24.00 0 66 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.642 NA NA NA
#> 2 age, Cure model -0.0169 NA NA NA
#> 3 grade_ii, Cure model 0.0696 NA NA NA
#> 4 grade_iii, Cure model 1.00 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0162 NA NA NA
#> 2 grade_ii, Survival model 0.421 NA NA NA
#> 3 grade_iii, Survival model 0.323 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.64161 -0.01693 0.06959 1.00442
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 250.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.64161367 -0.01692827 0.06958740 1.00441582
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01621068 0.42053521 0.32330140
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 5.088274e-01 5.983269e-01 4.838640e-02 6.329738e-02 3.537166e-02
#> [6] 3.685186e-01 7.343246e-01 2.189535e-01 3.537166e-02 1.915695e-02
#> [11] 3.092764e-02 1.668550e-01 4.600162e-01 5.340523e-01 8.799175e-01
#> [16] 8.799175e-01 3.252389e-01 8.799175e-01 2.950184e-01 8.570850e-02
#> [21] 2.277707e-02 4.018362e-01 3.685186e-01 7.978119e-02 2.950184e-01
#> [26] 8.056482e-01 2.007815e-01 3.574876e-01 4.247008e-01 5.337585e-02
#> [31] 5.337585e-02 2.097625e-01 2.373521e-01 1.179632e-01 1.046544e-01
#> [36] 1.364744e-03 1.589311e-02 2.848287e-03 5.983269e-01 1.056210e-02
#> [41] 7.201879e-01 4.247008e-01 5.723162e-01 1.179632e-01 1.179632e-01
#> [46] 2.752878e-01 6.329738e-02 2.850306e-01 1.056210e-02 5.723162e-01
#> [51] 9.543704e-01 7.909782e-01 3.685186e-01 8.570850e-02 1.179632e-01
#> [56] 6.377917e-01 9.846343e-01 4.480632e-01 1.046544e-01 1.835264e-01
#> [61] 8.499942e-01 4.840362e-01 7.343246e-01 7.408289e-02 5.213752e-01
#> [66] 2.563804e-01 4.963385e-01 2.189535e-01 8.799175e-01 2.950184e-01
#> [71] 2.563804e-01 1.750878e-01 4.600162e-01 9.543704e-01 3.465543e-01
#> [76] 6.648895e-01 6.922502e-01 6.513000e-01 2.468132e-01 9.804593e-02
#> [81] 7.611229e-03 8.204446e-01 5.983269e-01 3.252389e-01 3.537166e-02
#> [86] 1.835264e-01 7.343246e-01 1.179632e-01 8.499942e-01 5.023818e-03
#> [91] 7.061519e-01 6.990724e-05 2.671180e-02 5.340523e-01 6.648895e-01
#> [96] 4.018362e-01 5.206138e-04 1.179632e-01 1.179632e-01 7.343246e-01
#> [101] 5.340523e-01 8.351945e-01 9.391761e-01 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 96 155 90 68 36 130 52 108 99 66 153 76 188
#> 14.54 13.08 20.94 20.62 21.19 16.47 10.42 18.29 21.19 22.13 21.33 19.22 16.16
#> 81 149 149.1 23 149.2 45 158 175 192 130.1 150 45.1 145
#> 14.06 8.37 8.37 16.92 8.37 17.42 20.14 21.91 16.44 16.47 20.33 17.42 10.07
#> 8 171 5 190 190.1 88 41 55 170 168 15 164 155.1
#> 18.43 16.57 16.43 20.81 20.81 18.37 18.02 19.34 19.54 23.72 22.68 23.60 13.08
#> 63 107 5.1 60 58 58.1 111 68.1 30 63.1 60.1 25 93
#> 22.77 11.18 16.43 13.15 19.34 19.34 17.45 20.62 17.43 22.77 13.15 6.32 10.33
#> 130.2 158.1 58.2 123 91 79 170.1 179 16 180 52.1 128 13
#> 16.47 20.14 19.34 13.00 5.33 16.23 19.54 18.63 8.71 14.82 10.42 20.35 14.34
#> 117 133 108.1 149.3 45.2 117.1 97 188.1 25.1 106 140 49 14
#> 17.46 14.65 18.29 8.37 17.42 17.46 19.14 16.16 6.32 16.67 12.68 12.19 12.89
#> 134 166 92 101 155.2 23.1 99.1 179.1 52.2 58.3 16.1 129 43
#> 17.81 19.98 22.92 9.97 13.08 16.92 21.19 18.63 10.42 19.34 8.71 23.41 12.10
#> 78 139 81.1 140.1 85 86 55.1 55.2 52.3 81.2 187 70 191
#> 23.88 21.49 14.06 12.68 16.44 23.81 19.34 19.34 10.42 14.06 9.92 7.38 24.00
#> 35 172 2 138 74 132 83 185 191.1 75 28 7 83.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 148 156 161 65 137 48 102 182 185.1 182.1 165 120.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 178 72 48.1 20 1 80 21 103 193 156.1 98 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 126 74.1 67 46 62 178.1 152 119 44 103.1 186 82
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74.2 185.2 112 198 185.3 160 146 131.1 172.1 191.2 182.2 35.1 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 19 191.3 185.4 12.1 191.4 22 94 146.1 98.1 17 132.1 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198.1 116 147 46.1 35.2 46.2 122.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[51]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01625295 0.43007046 0.44976167
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.52488918 0.01199236 -0.09662949
#> grade_iii, Cure model
#> 0.57742660
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 188 16.16 1 46 0 1
#> 171 16.57 1 41 0 1
#> 187 9.92 1 39 1 0
#> 36 21.19 1 48 0 1
#> 61 10.12 1 36 0 1
#> 177 12.53 1 75 0 0
#> 154 12.63 1 20 1 0
#> 6 15.64 1 39 0 0
#> 51 18.23 1 83 0 1
#> 192 16.44 1 31 1 0
#> 88 18.37 1 47 0 0
#> 5 16.43 1 51 0 1
#> 14 12.89 1 21 0 0
#> 32 20.90 1 37 1 0
#> 23 16.92 1 61 0 0
#> 125 15.65 1 67 1 0
#> 5.1 16.43 1 51 0 1
#> 139 21.49 1 63 1 0
#> 164 23.60 1 76 0 1
#> 68 20.62 1 44 0 0
#> 40 18.00 1 28 1 0
#> 49 12.19 1 48 1 0
#> 5.2 16.43 1 51 0 1
#> 125.1 15.65 1 67 1 0
#> 61.1 10.12 1 36 0 1
#> 91 5.33 1 61 0 1
#> 4 17.64 1 NA 0 1
#> 29 15.45 1 68 1 0
#> 51.1 18.23 1 83 0 1
#> 88.1 18.37 1 47 0 0
#> 5.3 16.43 1 51 0 1
#> 145 10.07 1 65 1 0
#> 150 20.33 1 48 0 0
#> 15 22.68 1 48 0 0
#> 81 14.06 1 34 0 0
#> 139.1 21.49 1 63 1 0
#> 153 21.33 1 55 1 0
#> 18 15.21 1 49 1 0
#> 133 14.65 1 57 0 0
#> 96 14.54 1 33 0 1
#> 129 23.41 1 53 1 0
#> 6.1 15.64 1 39 0 0
#> 170 19.54 1 43 0 1
#> 140 12.68 1 59 1 0
#> 123 13.00 1 44 1 0
#> 111 17.45 1 47 0 1
#> 41 18.02 1 40 1 0
#> 91.1 5.33 1 61 0 1
#> 192.1 16.44 1 31 1 0
#> 166 19.98 1 48 0 0
#> 39 15.59 1 37 0 1
#> 13 14.34 1 54 0 1
#> 29.1 15.45 1 68 1 0
#> 91.2 5.33 1 61 0 1
#> 129.1 23.41 1 53 1 0
#> 96.1 14.54 1 33 0 1
#> 150.1 20.33 1 48 0 0
#> 184 17.77 1 38 0 0
#> 86 23.81 1 58 0 1
#> 36.1 21.19 1 48 0 1
#> 55 19.34 1 69 0 1
#> 56 12.21 1 60 0 0
#> 99 21.19 1 38 0 1
#> 168 23.72 1 70 0 0
#> 184.1 17.77 1 38 0 0
#> 70 7.38 1 30 1 0
#> 39.1 15.59 1 37 0 1
#> 101 9.97 1 10 0 1
#> 169 22.41 1 46 0 0
#> 66 22.13 1 53 0 0
#> 164.1 23.60 1 76 0 1
#> 167 15.55 1 56 1 0
#> 108 18.29 1 39 0 1
#> 39.2 15.59 1 37 0 1
#> 23.1 16.92 1 61 0 0
#> 170.1 19.54 1 43 0 1
#> 41.1 18.02 1 40 1 0
#> 197 21.60 1 69 1 0
#> 91.3 5.33 1 61 0 1
#> 4.1 17.64 1 NA 0 1
#> 58 19.34 1 39 0 0
#> 85 16.44 1 36 0 0
#> 199 19.81 1 NA 0 1
#> 36.2 21.19 1 48 0 1
#> 4.2 17.64 1 NA 0 1
#> 145.1 10.07 1 65 1 0
#> 70.1 7.38 1 30 1 0
#> 194 22.40 1 38 0 1
#> 177.1 12.53 1 75 0 0
#> 85.1 16.44 1 36 0 0
#> 175 21.91 1 43 0 0
#> 127 3.53 1 62 0 1
#> 155 13.08 1 26 0 0
#> 189 10.51 1 NA 1 0
#> 49.1 12.19 1 48 1 0
#> 197.1 21.60 1 69 1 0
#> 158 20.14 1 74 1 0
#> 91.4 5.33 1 61 0 1
#> 130 16.47 1 53 0 1
#> 170.2 19.54 1 43 0 1
#> 93 10.33 1 52 0 1
#> 171.1 16.57 1 41 0 1
#> 77 7.27 1 67 0 1
#> 24 23.89 1 38 0 0
#> 39.3 15.59 1 37 0 1
#> 184.2 17.77 1 38 0 0
#> 50 10.02 1 NA 1 0
#> 166.1 19.98 1 48 0 0
#> 32.1 20.90 1 37 1 0
#> 180 14.82 1 37 0 0
#> 113 22.86 1 34 0 0
#> 188.1 16.16 1 46 0 1
#> 35 24.00 0 51 0 0
#> 132 24.00 0 55 0 0
#> 152 24.00 0 36 0 1
#> 126 24.00 0 48 0 0
#> 20 24.00 0 46 1 0
#> 119 24.00 0 17 0 0
#> 193 24.00 0 45 0 1
#> 19 24.00 0 57 0 1
#> 141 24.00 0 44 1 0
#> 174 24.00 0 49 1 0
#> 147 24.00 0 76 1 0
#> 28 24.00 0 67 1 0
#> 132.1 24.00 0 55 0 0
#> 21 24.00 0 47 0 0
#> 104 24.00 0 50 1 0
#> 3 24.00 0 31 1 0
#> 119.1 24.00 0 17 0 0
#> 156 24.00 0 50 1 0
#> 162 24.00 0 51 0 0
#> 102 24.00 0 49 0 0
#> 84 24.00 0 39 0 1
#> 34 24.00 0 36 0 0
#> 22 24.00 0 52 1 0
#> 54 24.00 0 53 1 0
#> 165 24.00 0 47 0 0
#> 178 24.00 0 52 1 0
#> 65 24.00 0 57 1 0
#> 64 24.00 0 43 0 0
#> 112 24.00 0 61 0 0
#> 173 24.00 0 19 0 1
#> 193.1 24.00 0 45 0 1
#> 135 24.00 0 58 1 0
#> 144 24.00 0 28 0 1
#> 126.1 24.00 0 48 0 0
#> 185 24.00 0 44 1 0
#> 165.1 24.00 0 47 0 0
#> 163 24.00 0 66 0 0
#> 87 24.00 0 27 0 0
#> 198 24.00 0 66 0 1
#> 132.2 24.00 0 55 0 0
#> 193.2 24.00 0 45 0 1
#> 87.1 24.00 0 27 0 0
#> 48 24.00 0 31 1 0
#> 193.3 24.00 0 45 0 1
#> 115 24.00 0 NA 1 0
#> 174.1 24.00 0 49 1 0
#> 27 24.00 0 63 1 0
#> 67 24.00 0 25 0 0
#> 21.1 24.00 0 47 0 0
#> 185.1 24.00 0 44 1 0
#> 186 24.00 0 45 1 0
#> 33 24.00 0 53 0 0
#> 7 24.00 0 37 1 0
#> 109 24.00 0 48 0 0
#> 11 24.00 0 42 0 1
#> 198.1 24.00 0 66 0 1
#> 3.1 24.00 0 31 1 0
#> 3.2 24.00 0 31 1 0
#> 7.1 24.00 0 37 1 0
#> 67.1 24.00 0 25 0 0
#> 144.1 24.00 0 28 0 1
#> 115.1 24.00 0 NA 1 0
#> 191 24.00 0 60 0 1
#> 19.1 24.00 0 57 0 1
#> 19.2 24.00 0 57 0 1
#> 31 24.00 0 36 0 1
#> 20.1 24.00 0 46 1 0
#> 44 24.00 0 56 0 0
#> 160 24.00 0 31 1 0
#> 35.1 24.00 0 51 0 0
#> 22.1 24.00 0 52 1 0
#> 9 24.00 0 31 1 0
#> 191.1 24.00 0 60 0 1
#> 84.1 24.00 0 39 0 1
#> 33.1 24.00 0 53 0 0
#> 163.1 24.00 0 66 0 0
#> 163.2 24.00 0 66 0 0
#> 178.1 24.00 0 52 1 0
#> 112.1 24.00 0 61 0 0
#> 31.1 24.00 0 36 0 1
#> 135.1 24.00 0 58 1 0
#> 11.1 24.00 0 42 0 1
#> 147.1 24.00 0 76 1 0
#> 17 24.00 0 38 0 1
#> 132.3 24.00 0 55 0 0
#> 193.4 24.00 0 45 0 1
#> 28.1 24.00 0 67 1 0
#> 75 24.00 0 21 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.525 NA NA NA
#> 2 age, Cure model 0.0120 NA NA NA
#> 3 grade_ii, Cure model -0.0966 NA NA NA
#> 4 grade_iii, Cure model 0.577 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0163 NA NA NA
#> 2 grade_ii, Survival model 0.430 NA NA NA
#> 3 grade_iii, Survival model 0.450 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.52489 0.01199 -0.09663 0.57743
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.1
#> Residual Deviance: 258.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.52488918 0.01199236 -0.09662949 0.57742660
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01625295 0.43007046 0.44976167
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 4.083690e-01 2.952627e-01 8.589443e-01 5.745115e-02 7.898639e-01
#> [6] 7.090435e-01 6.960201e-01 4.527568e-01 1.937517e-01 3.256600e-01
#> [11] 1.687799e-01 3.662764e-01 6.700209e-01 7.873817e-02 2.754459e-01
#> [16] 4.302867e-01 3.662764e-01 4.155364e-02 2.688131e-03 9.049104e-02
#> [21] 2.290618e-01 7.490481e-01 3.662764e-01 4.302867e-01 7.898639e-01
#> [26] 9.147988e-01 5.331416e-01 1.937517e-01 1.687799e-01 3.662764e-01
#> [31] 8.172205e-01 9.678803e-02 1.355071e-02 6.316023e-01 4.155364e-02
#> [36] 5.181747e-02 5.571393e-01 5.816838e-01 5.941758e-01 6.223415e-03
#> [41] 4.527568e-01 1.312844e-01 6.829697e-01 6.571441e-01 2.657976e-01
#> [46] 2.112607e-01 9.147988e-01 3.256600e-01 1.168413e-01 4.757631e-01
#> [51] 6.189830e-01 5.331416e-01 9.147988e-01 6.223415e-03 5.941758e-01
#> [56] 9.678803e-02 2.381513e-01 5.708429e-04 5.745115e-02 1.531203e-01
#> [61] 7.355303e-01 5.745115e-02 1.361879e-03 2.381513e-01 8.729202e-01
#> [66] 4.757631e-01 8.450102e-01 1.675178e-02 2.397314e-02 2.688131e-03
#> [71] 5.212700e-01 1.852565e-01 4.757631e-01 2.754459e-01 1.312844e-01
#> [76] 2.112607e-01 3.231726e-02 9.147988e-01 1.531203e-01 3.256600e-01
#> [81] 5.745115e-02 8.172205e-01 8.729202e-01 2.031216e-02 7.090435e-01
#> [86] 3.256600e-01 2.798877e-02 9.853707e-01 6.443296e-01 7.490481e-01
#> [91] 3.231726e-02 1.098651e-01 9.147988e-01 3.153423e-01 1.312844e-01
#> [96] 7.761258e-01 2.952627e-01 9.006978e-01 8.935522e-05 4.757631e-01
#> [101] 2.381513e-01 1.168413e-01 7.873817e-02 5.693518e-01 1.071390e-02
#> [106] 4.083690e-01 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [191] 0.000000e+00 0.000000e+00
#>
#> $Time
#> 188 171 187 36 61 177 154 6 51 192 88 5 14
#> 16.16 16.57 9.92 21.19 10.12 12.53 12.63 15.64 18.23 16.44 18.37 16.43 12.89
#> 32 23 125 5.1 139 164 68 40 49 5.2 125.1 61.1 91
#> 20.90 16.92 15.65 16.43 21.49 23.60 20.62 18.00 12.19 16.43 15.65 10.12 5.33
#> 29 51.1 88.1 5.3 145 150 15 81 139.1 153 18 133 96
#> 15.45 18.23 18.37 16.43 10.07 20.33 22.68 14.06 21.49 21.33 15.21 14.65 14.54
#> 129 6.1 170 140 123 111 41 91.1 192.1 166 39 13 29.1
#> 23.41 15.64 19.54 12.68 13.00 17.45 18.02 5.33 16.44 19.98 15.59 14.34 15.45
#> 91.2 129.1 96.1 150.1 184 86 36.1 55 56 99 168 184.1 70
#> 5.33 23.41 14.54 20.33 17.77 23.81 21.19 19.34 12.21 21.19 23.72 17.77 7.38
#> 39.1 101 169 66 164.1 167 108 39.2 23.1 170.1 41.1 197 91.3
#> 15.59 9.97 22.41 22.13 23.60 15.55 18.29 15.59 16.92 19.54 18.02 21.60 5.33
#> 58 85 36.2 145.1 70.1 194 177.1 85.1 175 127 155 49.1 197.1
#> 19.34 16.44 21.19 10.07 7.38 22.40 12.53 16.44 21.91 3.53 13.08 12.19 21.60
#> 158 91.4 130 170.2 93 171.1 77 24 39.3 184.2 166.1 32.1 180
#> 20.14 5.33 16.47 19.54 10.33 16.57 7.27 23.89 15.59 17.77 19.98 20.90 14.82
#> 113 188.1 35 132 152 126 20 119 193 19 141 174 147
#> 22.86 16.16 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 132.1 21 104 3 119.1 156 162 102 84 34 22 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 178 65 64 112 173 193.1 135 144 126.1 185 165.1 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 198 132.2 193.2 87.1 48 193.3 174.1 27 67 21.1 185.1 186
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 7 109 11 198.1 3.1 3.2 7.1 67.1 144.1 191 19.1 19.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 20.1 44 160 35.1 22.1 9 191.1 84.1 33.1 163.1 163.2 178.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112.1 31.1 135.1 11.1 147.1 17 132.3 193.4 28.1 75
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[52]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01029388 0.54426054 0.14245376
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.514996627 0.008661096 0.231401866
#> grade_iii, Cure model
#> 0.700288648
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 81 14.06 1 34 0 0
#> 125 15.65 1 67 1 0
#> 184 17.77 1 38 0 0
#> 129 23.41 1 53 1 0
#> 86 23.81 1 58 0 1
#> 101 9.97 1 10 0 1
#> 85 16.44 1 36 0 0
#> 189 10.51 1 NA 1 0
#> 157 15.10 1 47 0 0
#> 130 16.47 1 53 0 1
#> 61 10.12 1 36 0 1
#> 124 9.73 1 NA 1 0
#> 114 13.68 1 NA 0 0
#> 99 21.19 1 38 0 1
#> 13 14.34 1 54 0 1
#> 81.1 14.06 1 34 0 0
#> 128 20.35 1 35 0 1
#> 184.1 17.77 1 38 0 0
#> 134 17.81 1 47 1 0
#> 129.1 23.41 1 53 1 0
#> 66 22.13 1 53 0 0
#> 37 12.52 1 57 1 0
#> 81.2 14.06 1 34 0 0
#> 69 23.23 1 25 0 1
#> 183 9.24 1 67 1 0
#> 13.1 14.34 1 54 0 1
#> 4 17.64 1 NA 0 1
#> 175 21.91 1 43 0 0
#> 43 12.10 1 61 0 1
#> 149 8.37 1 33 1 0
#> 150 20.33 1 48 0 0
#> 78 23.88 1 43 0 0
#> 30 17.43 1 78 0 0
#> 8 18.43 1 32 0 0
#> 150.1 20.33 1 48 0 0
#> 91 5.33 1 61 0 1
#> 52 10.42 1 52 0 1
#> 184.2 17.77 1 38 0 0
#> 89 11.44 1 NA 0 0
#> 139 21.49 1 63 1 0
#> 15 22.68 1 48 0 0
#> 55 19.34 1 69 0 1
#> 18 15.21 1 49 1 0
#> 130.1 16.47 1 53 0 1
#> 180 14.82 1 37 0 0
#> 166 19.98 1 48 0 0
#> 128.1 20.35 1 35 0 1
#> 129.2 23.41 1 53 1 0
#> 169 22.41 1 46 0 0
#> 37.1 12.52 1 57 1 0
#> 133 14.65 1 57 0 0
#> 194 22.40 1 38 0 1
#> 96 14.54 1 33 0 1
#> 29 15.45 1 68 1 0
#> 192 16.44 1 31 1 0
#> 8.1 18.43 1 32 0 0
#> 181 16.46 1 45 0 1
#> 68 20.62 1 44 0 0
#> 90 20.94 1 50 0 1
#> 91.1 5.33 1 61 0 1
#> 167 15.55 1 56 1 0
#> 164 23.60 1 76 0 1
#> 13.2 14.34 1 54 0 1
#> 37.2 12.52 1 57 1 0
#> 134.1 17.81 1 47 1 0
#> 97 19.14 1 65 0 1
#> 184.3 17.77 1 38 0 0
#> 49 12.19 1 48 1 0
#> 164.1 23.60 1 76 0 1
#> 40 18.00 1 28 1 0
#> 130.2 16.47 1 53 0 1
#> 76 19.22 1 54 0 1
#> 155 13.08 1 26 0 0
#> 5 16.43 1 51 0 1
#> 18.1 15.21 1 49 1 0
#> 60 13.15 1 38 1 0
#> 134.2 17.81 1 47 1 0
#> 69.1 23.23 1 25 0 1
#> 45 17.42 1 54 0 1
#> 164.2 23.60 1 76 0 1
#> 14 12.89 1 21 0 0
#> 175.1 21.91 1 43 0 0
#> 57 14.46 1 45 0 1
#> 128.2 20.35 1 35 0 1
#> 51 18.23 1 83 0 1
#> 123 13.00 1 44 1 0
#> 57.1 14.46 1 45 0 1
#> 59 10.16 1 NA 1 0
#> 194.1 22.40 1 38 0 1
#> 24 23.89 1 38 0 0
#> 177 12.53 1 75 0 0
#> 145 10.07 1 65 1 0
#> 92 22.92 1 47 0 1
#> 170 19.54 1 43 0 1
#> 5.1 16.43 1 51 0 1
#> 100 16.07 1 60 0 0
#> 125.1 15.65 1 67 1 0
#> 123.1 13.00 1 44 1 0
#> 60.1 13.15 1 38 1 0
#> 26 15.77 1 49 0 1
#> 50 10.02 1 NA 1 0
#> 97.1 19.14 1 65 0 1
#> 199 19.81 1 NA 0 1
#> 154 12.63 1 20 1 0
#> 93 10.33 1 52 0 1
#> 153 21.33 1 55 1 0
#> 130.3 16.47 1 53 0 1
#> 45.1 17.42 1 54 0 1
#> 155.1 13.08 1 26 0 0
#> 6 15.64 1 39 0 0
#> 66.1 22.13 1 53 0 0
#> 61.1 10.12 1 36 0 1
#> 163 24.00 0 66 0 0
#> 75 24.00 0 21 1 0
#> 162 24.00 0 51 0 0
#> 34 24.00 0 36 0 0
#> 152 24.00 0 36 0 1
#> 198 24.00 0 66 0 1
#> 38 24.00 0 31 1 0
#> 94 24.00 0 51 0 1
#> 73 24.00 0 NA 0 1
#> 112 24.00 0 61 0 0
#> 142 24.00 0 53 0 0
#> 53 24.00 0 32 0 1
#> 17 24.00 0 38 0 1
#> 151 24.00 0 42 0 0
#> 73.1 24.00 0 NA 0 1
#> 17.1 24.00 0 38 0 1
#> 151.1 24.00 0 42 0 0
#> 38.1 24.00 0 31 1 0
#> 102 24.00 0 49 0 0
#> 131 24.00 0 66 0 0
#> 185 24.00 0 44 1 0
#> 120 24.00 0 68 0 1
#> 196 24.00 0 19 0 0
#> 17.2 24.00 0 38 0 1
#> 12 24.00 0 63 0 0
#> 71 24.00 0 51 0 0
#> 151.2 24.00 0 42 0 0
#> 74 24.00 0 43 0 1
#> 122 24.00 0 66 0 0
#> 104 24.00 0 50 1 0
#> 12.1 24.00 0 63 0 0
#> 103 24.00 0 56 1 0
#> 172 24.00 0 41 0 0
#> 87 24.00 0 27 0 0
#> 35 24.00 0 51 0 0
#> 62 24.00 0 71 0 0
#> 98 24.00 0 34 1 0
#> 141 24.00 0 44 1 0
#> 122.1 24.00 0 66 0 0
#> 95 24.00 0 68 0 1
#> 3 24.00 0 31 1 0
#> 71.1 24.00 0 51 0 0
#> 172.1 24.00 0 41 0 0
#> 185.1 24.00 0 44 1 0
#> 200 24.00 0 64 0 0
#> 95.1 24.00 0 68 0 1
#> 2 24.00 0 9 0 0
#> 141.1 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 152.1 24.00 0 36 0 1
#> 116 24.00 0 58 0 1
#> 28 24.00 0 67 1 0
#> 193 24.00 0 45 0 1
#> 67 24.00 0 25 0 0
#> 135 24.00 0 58 1 0
#> 44 24.00 0 56 0 0
#> 193.1 24.00 0 45 0 1
#> 119 24.00 0 17 0 0
#> 185.2 24.00 0 44 1 0
#> 1 24.00 0 23 1 0
#> 9 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 98.1 24.00 0 34 1 0
#> 173 24.00 0 19 0 1
#> 95.2 24.00 0 68 0 1
#> 19 24.00 0 57 0 1
#> 27 24.00 0 63 1 0
#> 122.2 24.00 0 66 0 0
#> 144 24.00 0 28 0 1
#> 73.2 24.00 0 NA 0 1
#> 17.3 24.00 0 38 0 1
#> 161 24.00 0 45 0 0
#> 174 24.00 0 49 1 0
#> 126 24.00 0 48 0 0
#> 185.3 24.00 0 44 1 0
#> 112.1 24.00 0 61 0 0
#> 3.1 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 38.2 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 82 24.00 0 34 0 0
#> 172.2 24.00 0 41 0 0
#> 82.1 24.00 0 34 0 0
#> 191 24.00 0 60 0 1
#> 143 24.00 0 51 0 0
#> 156 24.00 0 50 1 0
#> 84.1 24.00 0 39 0 1
#> 48 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.515 NA NA NA
#> 2 age, Cure model 0.00866 NA NA NA
#> 3 grade_ii, Cure model 0.231 NA NA NA
#> 4 grade_iii, Cure model 0.700 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0103 NA NA NA
#> 2 grade_ii, Survival model 0.544 NA NA NA
#> 3 grade_iii, Survival model 0.142 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.514997 0.008661 0.231402 0.700289
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.1
#> Residual Deviance: 255 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.514996627 0.008661096 0.231401866 0.700288648
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01029388 0.54426054 0.14245376
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.6760712019 0.4953501743 0.3112240109 0.0256080593 0.0065691979
#> [6] 0.9386868336 0.4309046117 0.5729178043 0.3794735188 0.9021161088
#> [11] 0.1272748624 0.6413374521 0.6760712019 0.1509643605 0.3112240109
#> [16] 0.2834114217 0.0256080593 0.0834360261 0.8182371278 0.6760712019
#> [21] 0.0405373632 0.9509371853 0.6413374521 0.0973392658 0.8657601020
#> [26] 0.9632089362 0.1745592395 0.0030771870 0.3491895608 0.2452094573
#> [31] 0.1745592395 0.9754453028 0.8778247485 0.3112240109 0.1119935459
#> [36] 0.0576029104 0.2087618694 0.5507864845 0.3794735188 0.5841766809
#> [41] 0.1912684914 0.1509643605 0.0256080593 0.0639024916 0.8182371278
#> [46] 0.5955047139 0.0704457153 0.6069292135 0.5395889531 0.4309046117
#> [51] 0.2452094573 0.4202447727 0.1429129465 0.1350235002 0.9754453028
#> [56] 0.5284248376 0.0109609837 0.6413374521 0.8182371278 0.2834114217
#> [61] 0.2268083476 0.3112240109 0.8537597723 0.0109609837 0.2737593227
#> [66] 0.3794735188 0.2177217804 0.7349218294 0.4519902278 0.5507864845
#> [71] 0.7113403266 0.2834114217 0.0405373632 0.3592520297 0.0109609837
#> [76] 0.7823721055 0.0973392658 0.6183923445 0.1509643605 0.2640069381
#> [81] 0.7586824093 0.6183923445 0.0704457153 0.0007013907 0.8062427042
#> [86] 0.9264300371 0.0515613201 0.1999655534 0.4519902278 0.4733933520
#> [91] 0.4953501743 0.7586824093 0.7113403266 0.4843339748 0.2268083476
#> [96] 0.7943435087 0.8899435038 0.1196288366 0.3794735188 0.3592520297
#> [101] 0.7349218294 0.5172681988 0.0834360261 0.9021161088 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 81 125 184 129 86 101 85 157 130 61 99 13 81.1
#> 14.06 15.65 17.77 23.41 23.81 9.97 16.44 15.10 16.47 10.12 21.19 14.34 14.06
#> 128 184.1 134 129.1 66 37 81.2 69 183 13.1 175 43 149
#> 20.35 17.77 17.81 23.41 22.13 12.52 14.06 23.23 9.24 14.34 21.91 12.10 8.37
#> 150 78 30 8 150.1 91 52 184.2 139 15 55 18 130.1
#> 20.33 23.88 17.43 18.43 20.33 5.33 10.42 17.77 21.49 22.68 19.34 15.21 16.47
#> 180 166 128.1 129.2 169 37.1 133 194 96 29 192 8.1 181
#> 14.82 19.98 20.35 23.41 22.41 12.52 14.65 22.40 14.54 15.45 16.44 18.43 16.46
#> 68 90 91.1 167 164 13.2 37.2 134.1 97 184.3 49 164.1 40
#> 20.62 20.94 5.33 15.55 23.60 14.34 12.52 17.81 19.14 17.77 12.19 23.60 18.00
#> 130.2 76 155 5 18.1 60 134.2 69.1 45 164.2 14 175.1 57
#> 16.47 19.22 13.08 16.43 15.21 13.15 17.81 23.23 17.42 23.60 12.89 21.91 14.46
#> 128.2 51 123 57.1 194.1 24 177 145 92 170 5.1 100 125.1
#> 20.35 18.23 13.00 14.46 22.40 23.89 12.53 10.07 22.92 19.54 16.43 16.07 15.65
#> 123.1 60.1 26 97.1 154 93 153 130.3 45.1 155.1 6 66.1 61.1
#> 13.00 13.15 15.77 19.14 12.63 10.33 21.33 16.47 17.42 13.08 15.64 22.13 10.12
#> 163 75 162 34 152 198 38 94 112 142 53 17 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17.1 151.1 38.1 102 131 185 120 196 17.2 12 71 151.2 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 104 12.1 103 172 87 35 62 98 141 122.1 95 3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71.1 172.1 185.1 200 95.1 2 141.1 84 152.1 116 28 193 67
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 44 193.1 119 185.2 1 9 138 98.1 173 95.2 19 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122.2 144 17.3 161 174 126 185.3 112.1 3.1 176 38.2 46 82
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.2 82.1 191 143 156 84.1 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[53]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01975049 0.77899373 0.20981920
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.08850497 0.02198100 0.07497429
#> grade_iii, Cure model
#> 0.70665180
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 187 9.92 1 39 1 0
#> 16 8.71 1 71 0 1
#> 101 9.97 1 10 0 1
#> 26 15.77 1 49 0 1
#> 164 23.60 1 76 0 1
#> 25 6.32 1 34 1 0
#> 18 15.21 1 49 1 0
#> 140 12.68 1 59 1 0
#> 183 9.24 1 67 1 0
#> 145 10.07 1 65 1 0
#> 52 10.42 1 52 0 1
#> 197 21.60 1 69 1 0
#> 140.1 12.68 1 59 1 0
#> 41 18.02 1 40 1 0
#> 117 17.46 1 26 0 1
#> 157 15.10 1 47 0 0
#> 110 17.56 1 65 0 1
#> 192 16.44 1 31 1 0
#> 197.1 21.60 1 69 1 0
#> 99 21.19 1 38 0 1
#> 6 15.64 1 39 0 0
#> 113 22.86 1 34 0 0
#> 168 23.72 1 70 0 0
#> 52.1 10.42 1 52 0 1
#> 190 20.81 1 42 1 0
#> 188 16.16 1 46 0 1
#> 36 21.19 1 48 0 1
#> 180 14.82 1 37 0 0
#> 108 18.29 1 39 0 1
#> 29 15.45 1 68 1 0
#> 92 22.92 1 47 0 1
#> 168.1 23.72 1 70 0 0
#> 159 10.55 1 50 0 1
#> 154 12.63 1 20 1 0
#> 41.1 18.02 1 40 1 0
#> 89 11.44 1 NA 0 0
#> 59 10.16 1 NA 1 0
#> 26.1 15.77 1 49 0 1
#> 56 12.21 1 60 0 0
#> 108.1 18.29 1 39 0 1
#> 99.1 21.19 1 38 0 1
#> 25.1 6.32 1 34 1 0
#> 190.1 20.81 1 42 1 0
#> 105 19.75 1 60 0 0
#> 113.1 22.86 1 34 0 0
#> 123 13.00 1 44 1 0
#> 111 17.45 1 47 0 1
#> 76 19.22 1 54 0 1
#> 52.2 10.42 1 52 0 1
#> 125 15.65 1 67 1 0
#> 149 8.37 1 33 1 0
#> 129 23.41 1 53 1 0
#> 30 17.43 1 78 0 0
#> 4 17.64 1 NA 0 1
#> 136 21.83 1 43 0 1
#> 125.1 15.65 1 67 1 0
#> 23 16.92 1 61 0 0
#> 169 22.41 1 46 0 0
#> 117.1 17.46 1 26 0 1
#> 26.2 15.77 1 49 0 1
#> 49 12.19 1 48 1 0
#> 55 19.34 1 69 0 1
#> 96 14.54 1 33 0 1
#> 88 18.37 1 47 0 0
#> 30.1 17.43 1 78 0 0
#> 39 15.59 1 37 0 1
#> 113.2 22.86 1 34 0 0
#> 158 20.14 1 74 1 0
#> 167 15.55 1 56 1 0
#> 57 14.46 1 45 0 1
#> 107 11.18 1 54 1 0
#> 70 7.38 1 30 1 0
#> 180.1 14.82 1 37 0 0
#> 101.1 9.97 1 10 0 1
#> 79 16.23 1 54 1 0
#> 8 18.43 1 32 0 0
#> 106 16.67 1 49 1 0
#> 51 18.23 1 83 0 1
#> 171 16.57 1 41 0 1
#> 181 16.46 1 45 0 1
#> 179 18.63 1 42 0 0
#> 8.1 18.43 1 32 0 0
#> 133 14.65 1 57 0 0
#> 61 10.12 1 36 0 1
#> 36.1 21.19 1 48 0 1
#> 92.1 22.92 1 47 0 1
#> 86 23.81 1 58 0 1
#> 79.1 16.23 1 54 1 0
#> 140.2 12.68 1 59 1 0
#> 101.2 9.97 1 10 0 1
#> 140.3 12.68 1 59 1 0
#> 180.2 14.82 1 37 0 0
#> 77 7.27 1 67 0 1
#> 10 10.53 1 34 0 0
#> 130 16.47 1 53 0 1
#> 91 5.33 1 61 0 1
#> 89.1 11.44 1 NA 0 0
#> 180.3 14.82 1 37 0 0
#> 59.1 10.16 1 NA 1 0
#> 187.1 9.92 1 39 1 0
#> 79.2 16.23 1 54 1 0
#> 55.1 19.34 1 69 0 1
#> 56.1 12.21 1 60 0 0
#> 61.1 10.12 1 36 0 1
#> 36.2 21.19 1 48 0 1
#> 139 21.49 1 63 1 0
#> 107.1 11.18 1 54 1 0
#> 8.2 18.43 1 32 0 0
#> 199 19.81 1 NA 0 1
#> 99.2 21.19 1 38 0 1
#> 52.3 10.42 1 52 0 1
#> 194 22.40 1 38 0 1
#> 191 24.00 0 60 0 1
#> 109 24.00 0 48 0 0
#> 54 24.00 0 53 1 0
#> 137 24.00 0 45 1 0
#> 84 24.00 0 39 0 1
#> 73 24.00 0 NA 0 1
#> 48 24.00 0 31 1 0
#> 137.1 24.00 0 45 1 0
#> 141 24.00 0 44 1 0
#> 22 24.00 0 52 1 0
#> 34 24.00 0 36 0 0
#> 46 24.00 0 71 0 0
#> 161 24.00 0 45 0 0
#> 182 24.00 0 35 0 0
#> 144 24.00 0 28 0 1
#> 80 24.00 0 41 0 0
#> 7 24.00 0 37 1 0
#> 193 24.00 0 45 0 1
#> 1 24.00 0 23 1 0
#> 135 24.00 0 58 1 0
#> 82 24.00 0 34 0 0
#> 138 24.00 0 44 1 0
#> 83 24.00 0 6 0 0
#> 3 24.00 0 31 1 0
#> 116 24.00 0 58 0 1
#> 198 24.00 0 66 0 1
#> 53 24.00 0 32 0 1
#> 31 24.00 0 36 0 1
#> 64 24.00 0 43 0 0
#> 151 24.00 0 42 0 0
#> 22.1 24.00 0 52 1 0
#> 138.1 24.00 0 44 1 0
#> 28 24.00 0 67 1 0
#> 176 24.00 0 43 0 1
#> 31.1 24.00 0 36 0 1
#> 186 24.00 0 45 1 0
#> 20 24.00 0 46 1 0
#> 104 24.00 0 50 1 0
#> 22.2 24.00 0 52 1 0
#> 71 24.00 0 51 0 0
#> 144.1 24.00 0 28 0 1
#> 19 24.00 0 57 0 1
#> 146 24.00 0 63 1 0
#> 11 24.00 0 42 0 1
#> 54.1 24.00 0 53 1 0
#> 185 24.00 0 44 1 0
#> 142 24.00 0 53 0 0
#> 35 24.00 0 51 0 0
#> 119 24.00 0 17 0 0
#> 87 24.00 0 27 0 0
#> 173 24.00 0 19 0 1
#> 152 24.00 0 36 0 1
#> 53.1 24.00 0 32 0 1
#> 173.1 24.00 0 19 0 1
#> 72 24.00 0 40 0 1
#> 163 24.00 0 66 0 0
#> 132 24.00 0 55 0 0
#> 165 24.00 0 47 0 0
#> 120 24.00 0 68 0 1
#> 148 24.00 0 61 1 0
#> 102 24.00 0 49 0 0
#> 132.1 24.00 0 55 0 0
#> 1.1 24.00 0 23 1 0
#> 141.1 24.00 0 44 1 0
#> 20.1 24.00 0 46 1 0
#> 186.1 24.00 0 45 1 0
#> 141.2 24.00 0 44 1 0
#> 35.1 24.00 0 51 0 0
#> 3.1 24.00 0 31 1 0
#> 182.1 24.00 0 35 0 0
#> 144.2 24.00 0 28 0 1
#> 163.1 24.00 0 66 0 0
#> 67 24.00 0 25 0 0
#> 74 24.00 0 43 0 1
#> 53.2 24.00 0 32 0 1
#> 104.1 24.00 0 50 1 0
#> 161.1 24.00 0 45 0 0
#> 118 24.00 0 44 1 0
#> 131 24.00 0 66 0 0
#> 185.1 24.00 0 44 1 0
#> 19.1 24.00 0 57 0 1
#> 31.2 24.00 0 36 0 1
#> 95 24.00 0 68 0 1
#> 147 24.00 0 76 1 0
#> 118.1 24.00 0 44 1 0
#> 138.2 24.00 0 44 1 0
#> 73.1 24.00 0 NA 0 1
#> 82.1 24.00 0 34 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.09 NA NA NA
#> 2 age, Cure model 0.0220 NA NA NA
#> 3 grade_ii, Cure model 0.0750 NA NA NA
#> 4 grade_iii, Cure model 0.707 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0198 NA NA NA
#> 2 grade_ii, Survival model 0.779 NA NA NA
#> 3 grade_iii, Survival model 0.210 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.08850 0.02198 0.07497 0.70665
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.1
#> Residual Deviance: 255.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.08850497 0.02198100 0.07497429 0.70665180
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01975049 0.77899373 0.20981920
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 8.455822e-01 8.911919e-01 8.006121e-01 3.109118e-01 7.839528e-04
#> [6] 9.533639e-01 4.102035e-01 5.343631e-01 8.758252e-01 7.853216e-01
#> [11] 6.972489e-01 2.112271e-02 5.343631e-01 1.480445e-01 1.713188e-01
#> [16] 4.219382e-01 1.632678e-01 2.614088e-01 2.112271e-02 3.191589e-02
#> [21] 3.642617e-01 6.149763e-03 8.373778e-05 6.972489e-01 5.540111e-02
#> [26] 3.006221e-01 3.191589e-02 4.338736e-01 1.256543e-01 3.985263e-01
#> [31] 3.092383e-03 8.373778e-05 6.688054e-01 5.866066e-01 1.480445e-01
#> [36] 3.109118e-01 5.999835e-01 1.256543e-01 3.191589e-02 9.533639e-01
#> [41] 5.540111e-02 6.984985e-02 6.149763e-03 5.212227e-01 1.874306e-01
#> [46] 8.653366e-02 6.972489e-01 3.423774e-01 9.067453e-01 1.843992e-03
#> [51] 1.958573e-01 1.785751e-02 3.423774e-01 2.135167e-01 1.208281e-02
#> [56] 1.713188e-01 3.109118e-01 6.272746e-01 7.518264e-02 4.951637e-01
#> [61] 1.185062e-01 1.958573e-01 3.755584e-01 6.149763e-03 6.478553e-02
#> [66] 3.869948e-01 5.081109e-01 6.411193e-01 9.222627e-01 4.338736e-01
#> [71] 8.006121e-01 2.712850e-01 9.899770e-02 2.228119e-01 1.402362e-01
#> [76] 2.321743e-01 2.514645e-01 9.264753e-02 9.899770e-02 4.823364e-01
#> [81] 7.552682e-01 3.191589e-02 3.092383e-03 6.544790e-06 2.712850e-01
#> [86] 5.343631e-01 8.006121e-01 5.343631e-01 4.338736e-01 9.377267e-01
#> [91] 6.829547e-01 2.417103e-01 9.842679e-01 4.338736e-01 8.455822e-01
#> [96] 2.712850e-01 7.518264e-02 5.999835e-01 7.552682e-01 3.191589e-02
#> [101] 2.802816e-02 6.411193e-01 9.899770e-02 3.191589e-02 6.972489e-01
#> [106] 1.485262e-02 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [191] 0.000000e+00 0.000000e+00
#>
#> $Time
#> 187 16 101 26 164 25 18 140 183 145 52 197 140.1
#> 9.92 8.71 9.97 15.77 23.60 6.32 15.21 12.68 9.24 10.07 10.42 21.60 12.68
#> 41 117 157 110 192 197.1 99 6 113 168 52.1 190 188
#> 18.02 17.46 15.10 17.56 16.44 21.60 21.19 15.64 22.86 23.72 10.42 20.81 16.16
#> 36 180 108 29 92 168.1 159 154 41.1 26.1 56 108.1 99.1
#> 21.19 14.82 18.29 15.45 22.92 23.72 10.55 12.63 18.02 15.77 12.21 18.29 21.19
#> 25.1 190.1 105 113.1 123 111 76 52.2 125 149 129 30 136
#> 6.32 20.81 19.75 22.86 13.00 17.45 19.22 10.42 15.65 8.37 23.41 17.43 21.83
#> 125.1 23 169 117.1 26.2 49 55 96 88 30.1 39 113.2 158
#> 15.65 16.92 22.41 17.46 15.77 12.19 19.34 14.54 18.37 17.43 15.59 22.86 20.14
#> 167 57 107 70 180.1 101.1 79 8 106 51 171 181 179
#> 15.55 14.46 11.18 7.38 14.82 9.97 16.23 18.43 16.67 18.23 16.57 16.46 18.63
#> 8.1 133 61 36.1 92.1 86 79.1 140.2 101.2 140.3 180.2 77 10
#> 18.43 14.65 10.12 21.19 22.92 23.81 16.23 12.68 9.97 12.68 14.82 7.27 10.53
#> 130 91 180.3 187.1 79.2 55.1 56.1 61.1 36.2 139 107.1 8.2 99.2
#> 16.47 5.33 14.82 9.92 16.23 19.34 12.21 10.12 21.19 21.49 11.18 18.43 21.19
#> 52.3 194 191 109 54 137 84 48 137.1 141 22 34 46
#> 10.42 22.40 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 182 144 80 7 193 1 135 82 138 83 3 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 53 31 64 151 22.1 138.1 28 176 31.1 186 20 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22.2 71 144.1 19 146 11 54.1 185 142 35 119 87 173
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 53.1 173.1 72 163 132 165 120 148 102 132.1 1.1 141.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20.1 186.1 141.2 35.1 3.1 182.1 144.2 163.1 67 74 53.2 104.1 161.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 131 185.1 19.1 31.2 95 147 118.1 138.2 82.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[54]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01761593 0.51042932 0.72572498
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.93472795 0.01064269 0.23593220
#> grade_iii, Cure model
#> 1.70739520
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 85 16.44 1 36 0 0
#> 40 18.00 1 28 1 0
#> 114 13.68 1 NA 0 0
#> 39 15.59 1 37 0 1
#> 179 18.63 1 42 0 0
#> 194 22.40 1 38 0 1
#> 57 14.46 1 45 0 1
#> 155 13.08 1 26 0 0
#> 123 13.00 1 44 1 0
#> 39.1 15.59 1 37 0 1
#> 123.1 13.00 1 44 1 0
#> 8 18.43 1 32 0 0
#> 197 21.60 1 69 1 0
#> 14 12.89 1 21 0 0
#> 60 13.15 1 38 1 0
#> 181 16.46 1 45 0 1
#> 61 10.12 1 36 0 1
#> 91 5.33 1 61 0 1
#> 184 17.77 1 38 0 0
#> 197.1 21.60 1 69 1 0
#> 127 3.53 1 62 0 1
#> 42 12.43 1 49 0 1
#> 188 16.16 1 46 0 1
#> 164 23.60 1 76 0 1
#> 96 14.54 1 33 0 1
#> 175 21.91 1 43 0 0
#> 164.1 23.60 1 76 0 1
#> 42.1 12.43 1 49 0 1
#> 42.2 12.43 1 49 0 1
#> 13 14.34 1 54 0 1
#> 110 17.56 1 65 0 1
#> 42.3 12.43 1 49 0 1
#> 111 17.45 1 47 0 1
#> 129 23.41 1 53 1 0
#> 52 10.42 1 52 0 1
#> 93 10.33 1 52 0 1
#> 89 11.44 1 NA 0 0
#> 108 18.29 1 39 0 1
#> 25 6.32 1 34 1 0
#> 125 15.65 1 67 1 0
#> 93.1 10.33 1 52 0 1
#> 16 8.71 1 71 0 1
#> 93.2 10.33 1 52 0 1
#> 169 22.41 1 46 0 0
#> 93.3 10.33 1 52 0 1
#> 164.2 23.60 1 76 0 1
#> 14.1 12.89 1 21 0 0
#> 30 17.43 1 78 0 0
#> 153 21.33 1 55 1 0
#> 61.1 10.12 1 36 0 1
#> 59 10.16 1 NA 1 0
#> 107 11.18 1 54 1 0
#> 149 8.37 1 33 1 0
#> 127.1 3.53 1 62 0 1
#> 177 12.53 1 75 0 0
#> 168 23.72 1 70 0 0
#> 55 19.34 1 69 0 1
#> 66 22.13 1 53 0 0
#> 24 23.89 1 38 0 0
#> 170 19.54 1 43 0 1
#> 159 10.55 1 50 0 1
#> 124 9.73 1 NA 1 0
#> 159.1 10.55 1 50 0 1
#> 39.2 15.59 1 37 0 1
#> 42.4 12.43 1 49 0 1
#> 32 20.90 1 37 1 0
#> 111.1 17.45 1 47 0 1
#> 101 9.97 1 10 0 1
#> 107.1 11.18 1 54 1 0
#> 105 19.75 1 60 0 0
#> 195 11.76 1 NA 1 0
#> 77 7.27 1 67 0 1
#> 63 22.77 1 31 1 0
#> 150 20.33 1 48 0 0
#> 23 16.92 1 61 0 0
#> 111.2 17.45 1 47 0 1
#> 145 10.07 1 65 1 0
#> 70 7.38 1 30 1 0
#> 6 15.64 1 39 0 0
#> 134 17.81 1 47 1 0
#> 23.1 16.92 1 61 0 0
#> 157 15.10 1 47 0 0
#> 189 10.51 1 NA 1 0
#> 4 17.64 1 NA 0 1
#> 153.1 21.33 1 55 1 0
#> 111.3 17.45 1 47 0 1
#> 99 21.19 1 38 0 1
#> 168.1 23.72 1 70 0 0
#> 154 12.63 1 20 1 0
#> 59.1 10.16 1 NA 1 0
#> 32.1 20.90 1 37 1 0
#> 129.1 23.41 1 53 1 0
#> 45 17.42 1 54 0 1
#> 36 21.19 1 48 0 1
#> 190 20.81 1 42 1 0
#> 97 19.14 1 65 0 1
#> 50 10.02 1 NA 1 0
#> 171 16.57 1 41 0 1
#> 42.5 12.43 1 49 0 1
#> 183 9.24 1 67 1 0
#> 171.1 16.57 1 41 0 1
#> 43 12.10 1 61 0 1
#> 194.1 22.40 1 38 0 1
#> 189.1 10.51 1 NA 1 0
#> 77.1 7.27 1 67 0 1
#> 49 12.19 1 48 1 0
#> 60.1 13.15 1 38 1 0
#> 41 18.02 1 40 1 0
#> 136 21.83 1 43 0 1
#> 70.1 7.38 1 30 1 0
#> 18 15.21 1 49 1 0
#> 70.2 7.38 1 30 1 0
#> 138 24.00 0 44 1 0
#> 38 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 20 24.00 0 46 1 0
#> 141 24.00 0 44 1 0
#> 142 24.00 0 53 0 0
#> 137 24.00 0 45 1 0
#> 72 24.00 0 40 0 1
#> 165 24.00 0 47 0 0
#> 156 24.00 0 50 1 0
#> 116 24.00 0 58 0 1
#> 174 24.00 0 49 1 0
#> 193 24.00 0 45 0 1
#> 28 24.00 0 67 1 0
#> 103 24.00 0 56 1 0
#> 3 24.00 0 31 1 0
#> 198 24.00 0 66 0 1
#> 119 24.00 0 17 0 0
#> 54 24.00 0 53 1 0
#> 82 24.00 0 34 0 0
#> 80 24.00 0 41 0 0
#> 185 24.00 0 44 1 0
#> 191 24.00 0 60 0 1
#> 75 24.00 0 21 1 0
#> 182 24.00 0 35 0 0
#> 87 24.00 0 27 0 0
#> 20.1 24.00 0 46 1 0
#> 28.1 24.00 0 67 1 0
#> 122 24.00 0 66 0 0
#> 34 24.00 0 36 0 0
#> 7 24.00 0 37 1 0
#> 83 24.00 0 6 0 0
#> 196 24.00 0 19 0 0
#> 121 24.00 0 57 1 0
#> 162 24.00 0 51 0 0
#> 67 24.00 0 25 0 0
#> 84 24.00 0 39 0 1
#> 12 24.00 0 63 0 0
#> 54.1 24.00 0 53 1 0
#> 22 24.00 0 52 1 0
#> 53 24.00 0 32 0 1
#> 112 24.00 0 61 0 0
#> 141.1 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 72.1 24.00 0 40 0 1
#> 102 24.00 0 49 0 0
#> 54.2 24.00 0 53 1 0
#> 186 24.00 0 45 1 0
#> 75.1 24.00 0 21 1 0
#> 12.1 24.00 0 63 0 0
#> 163 24.00 0 66 0 0
#> 2 24.00 0 9 0 0
#> 172 24.00 0 41 0 0
#> 48 24.00 0 31 1 0
#> 65 24.00 0 57 1 0
#> 191.1 24.00 0 60 0 1
#> 160 24.00 0 31 1 0
#> 131 24.00 0 66 0 0
#> 72.2 24.00 0 40 0 1
#> 7.1 24.00 0 37 1 0
#> 156.1 24.00 0 50 1 0
#> 162.1 24.00 0 51 0 0
#> 151 24.00 0 42 0 0
#> 172.1 24.00 0 41 0 0
#> 122.1 24.00 0 66 0 0
#> 31.1 24.00 0 36 0 1
#> 28.2 24.00 0 67 1 0
#> 162.2 24.00 0 51 0 0
#> 163.1 24.00 0 66 0 0
#> 146 24.00 0 63 1 0
#> 186.1 24.00 0 45 1 0
#> 2.1 24.00 0 9 0 0
#> 148 24.00 0 61 1 0
#> 182.1 24.00 0 35 0 0
#> 132 24.00 0 55 0 0
#> 38.1 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 115 24.00 0 NA 1 0
#> 87.1 24.00 0 27 0 0
#> 151.1 24.00 0 42 0 0
#> 200 24.00 0 64 0 0
#> 115.1 24.00 0 NA 1 0
#> 31.2 24.00 0 36 0 1
#> 135 24.00 0 58 1 0
#> 9 24.00 0 31 1 0
#> 191.2 24.00 0 60 0 1
#> 115.2 24.00 0 NA 1 0
#> 115.3 24.00 0 NA 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.935 NA NA NA
#> 2 age, Cure model 0.0106 NA NA NA
#> 3 grade_ii, Cure model 0.236 NA NA NA
#> 4 grade_iii, Cure model 1.71 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0176 NA NA NA
#> 2 grade_ii, Survival model 0.510 NA NA NA
#> 3 grade_iii, Survival model 0.726 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.93473 0.01064 0.23593 1.70740
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.1
#> Residual Deviance: 231.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.93472795 0.01064269 0.23593220 1.70739520
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01761593 0.51042932 0.72572498
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.3597962997 0.2111169428 0.4035844446 0.1740505979 0.0350565664
#> [6] 0.4695932943 0.5147229601 0.5262109299 0.4035844446 0.5262109299
#> [11] 0.1831573772 0.0648994546 0.5491667264 0.4921861752 0.3491340344
#> [16] 0.7990695282 0.9616348150 0.2299415591 0.0648994546 0.9744108614
#> [21] 0.5960131850 0.3706090586 0.0048238348 0.4583411595 0.0518052967
#> [26] 0.0048238348 0.5960131850 0.5960131850 0.4808629389 0.2396026762
#> [31] 0.5960131850 0.2493991186 0.0145354007 0.7378706204 0.7502435005
#> [36] 0.1924635989 0.9489085636 0.3814474921 0.7502435005 0.8612467186
#> [41] 0.7502435005 0.0291693298 0.7502435005 0.0048238348 0.5491667264
#> [46] 0.2868847597 0.0786987562 0.7990695282 0.6890550798 0.8738195689
#> [51] 0.9744108614 0.5841309007 0.0007762491 0.1564821580 0.0456808941
#> [56] 0.0001101010 0.1479615664 0.7134028386 0.7134028386 0.4035844446
#> [61] 0.5960131850 0.1082783678 0.2493991186 0.8363392821 0.6890550798
#> [66] 0.1394564169 0.9236552386 0.0238767124 0.1312768168 0.3072137592
#> [71] 0.2493991186 0.8237938271 0.8864048157 0.3924384017 0.2204745733
#> [76] 0.3072137592 0.4470459645 0.0786987562 0.2493991186 0.0934539815
#> [81] 0.0007762491 0.5724232302 0.1082783678 0.0145354007 0.2970141287
#> [86] 0.0934539815 0.1233781457 0.1651863534 0.3281759961 0.5960131850
#> [91] 0.8487483940 0.3281759961 0.6769259209 0.0350565664 0.9236552386
#> [96] 0.6648604335 0.4921861752 0.2017521874 0.0583405164 0.8864048157
#> [101] 0.4359092110 0.8864048157 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000
#>
#> $Time
#> 85 40 39 179 194 57 155 123 39.1 123.1 8 197 14
#> 16.44 18.00 15.59 18.63 22.40 14.46 13.08 13.00 15.59 13.00 18.43 21.60 12.89
#> 60 181 61 91 184 197.1 127 42 188 164 96 175 164.1
#> 13.15 16.46 10.12 5.33 17.77 21.60 3.53 12.43 16.16 23.60 14.54 21.91 23.60
#> 42.1 42.2 13 110 42.3 111 129 52 93 108 25 125 93.1
#> 12.43 12.43 14.34 17.56 12.43 17.45 23.41 10.42 10.33 18.29 6.32 15.65 10.33
#> 16 93.2 169 93.3 164.2 14.1 30 153 61.1 107 149 127.1 177
#> 8.71 10.33 22.41 10.33 23.60 12.89 17.43 21.33 10.12 11.18 8.37 3.53 12.53
#> 168 55 66 24 170 159 159.1 39.2 42.4 32 111.1 101 107.1
#> 23.72 19.34 22.13 23.89 19.54 10.55 10.55 15.59 12.43 20.90 17.45 9.97 11.18
#> 105 77 63 150 23 111.2 145 70 6 134 23.1 157 153.1
#> 19.75 7.27 22.77 20.33 16.92 17.45 10.07 7.38 15.64 17.81 16.92 15.10 21.33
#> 111.3 99 168.1 154 32.1 129.1 45 36 190 97 171 42.5 183
#> 17.45 21.19 23.72 12.63 20.90 23.41 17.42 21.19 20.81 19.14 16.57 12.43 9.24
#> 171.1 43 194.1 77.1 49 60.1 41 136 70.1 18 70.2 138 38
#> 16.57 12.10 22.40 7.27 12.19 13.15 18.02 21.83 7.38 15.21 7.38 24.00 24.00
#> 118 20 141 142 137 72 165 156 116 174 193 28 103
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 198 119 54 82 80 185 191 75 182 87 20.1 28.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 34 7 83 196 121 162 67 84 12 54.1 22 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 141.1 31 72.1 102 54.2 186 75.1 12.1 163 2 172 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65 191.1 160 131 72.2 7.1 156.1 162.1 151 172.1 122.1 31.1 28.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162.2 163.1 146 186.1 2.1 148 182.1 132 38.1 104 87.1 151.1 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31.2 135 9 191.2
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[55]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004314454 0.920662002 0.436228832
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.95404430 0.01413929 0.24047235
#> grade_iii, Cure model
#> 1.06603712
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 96 14.54 1 33 0 1
#> 39 15.59 1 37 0 1
#> 45 17.42 1 54 0 1
#> 108 18.29 1 39 0 1
#> 50 10.02 1 NA 1 0
#> 101 9.97 1 10 0 1
#> 8 18.43 1 32 0 0
#> 36 21.19 1 48 0 1
#> 26 15.77 1 49 0 1
#> 89 11.44 1 NA 0 0
#> 183 9.24 1 67 1 0
#> 105 19.75 1 60 0 0
#> 61 10.12 1 36 0 1
#> 92 22.92 1 47 0 1
#> 69 23.23 1 25 0 1
#> 194 22.40 1 38 0 1
#> 113 22.86 1 34 0 0
#> 78 23.88 1 43 0 0
#> 99 21.19 1 38 0 1
#> 179 18.63 1 42 0 0
#> 124 9.73 1 NA 1 0
#> 13 14.34 1 54 0 1
#> 187 9.92 1 39 1 0
#> 181 16.46 1 45 0 1
#> 13.1 14.34 1 54 0 1
#> 92.1 22.92 1 47 0 1
#> 194.1 22.40 1 38 0 1
#> 197 21.60 1 69 1 0
#> 105.1 19.75 1 60 0 0
#> 40 18.00 1 28 1 0
#> 164 23.60 1 76 0 1
#> 127 3.53 1 62 0 1
#> 110 17.56 1 65 0 1
#> 130 16.47 1 53 0 1
#> 70 7.38 1 30 1 0
#> 188 16.16 1 46 0 1
#> 93 10.33 1 52 0 1
#> 159 10.55 1 50 0 1
#> 5 16.43 1 51 0 1
#> 155 13.08 1 26 0 0
#> 92.2 22.92 1 47 0 1
#> 175 21.91 1 43 0 0
#> 14 12.89 1 21 0 0
#> 134 17.81 1 47 1 0
#> 190 20.81 1 42 1 0
#> 149 8.37 1 33 1 0
#> 133 14.65 1 57 0 0
#> 168 23.72 1 70 0 0
#> 113.1 22.86 1 34 0 0
#> 52 10.42 1 52 0 1
#> 89.1 11.44 1 NA 0 0
#> 133.1 14.65 1 57 0 0
#> 40.1 18.00 1 28 1 0
#> 97 19.14 1 65 0 1
#> 124.1 9.73 1 NA 1 0
#> 61.1 10.12 1 36 0 1
#> 16 8.71 1 71 0 1
#> 192 16.44 1 31 1 0
#> 111 17.45 1 47 0 1
#> 140 12.68 1 59 1 0
#> 133.2 14.65 1 57 0 0
#> 25 6.32 1 34 1 0
#> 55 19.34 1 69 0 1
#> 60 13.15 1 38 1 0
#> 168.1 23.72 1 70 0 0
#> 125 15.65 1 67 1 0
#> 155.1 13.08 1 26 0 0
#> 29 15.45 1 68 1 0
#> 111.1 17.45 1 47 0 1
#> 177 12.53 1 75 0 0
#> 168.2 23.72 1 70 0 0
#> 136 21.83 1 43 0 1
#> 171 16.57 1 41 0 1
#> 49 12.19 1 48 1 0
#> 10 10.53 1 34 0 0
#> 63 22.77 1 31 1 0
#> 45.1 17.42 1 54 0 1
#> 128 20.35 1 35 0 1
#> 195 11.76 1 NA 1 0
#> 42 12.43 1 49 0 1
#> 13.2 14.34 1 54 0 1
#> 136.1 21.83 1 43 0 1
#> 110.1 17.56 1 65 0 1
#> 199 19.81 1 NA 0 1
#> 184 17.77 1 38 0 0
#> 110.2 17.56 1 65 0 1
#> 68 20.62 1 44 0 0
#> 199.1 19.81 1 NA 0 1
#> 5.1 16.43 1 51 0 1
#> 181.1 16.46 1 45 0 1
#> 136.2 21.83 1 43 0 1
#> 105.2 19.75 1 60 0 0
#> 79 16.23 1 54 1 0
#> 171.1 16.57 1 41 0 1
#> 100 16.07 1 60 0 0
#> 99.1 21.19 1 38 0 1
#> 166 19.98 1 48 0 0
#> 175.1 21.91 1 43 0 0
#> 187.1 9.92 1 39 1 0
#> 153 21.33 1 55 1 0
#> 117 17.46 1 26 0 1
#> 49.1 12.19 1 48 1 0
#> 105.3 19.75 1 60 0 0
#> 26.1 15.77 1 49 0 1
#> 56 12.21 1 60 0 0
#> 183.1 9.24 1 67 1 0
#> 139 21.49 1 63 1 0
#> 188.1 16.16 1 46 0 1
#> 130.1 16.47 1 53 0 1
#> 8.1 18.43 1 32 0 0
#> 145 10.07 1 65 1 0
#> 79.1 16.23 1 54 1 0
#> 172 24.00 0 41 0 0
#> 72 24.00 0 40 0 1
#> 17 24.00 0 38 0 1
#> 120 24.00 0 68 0 1
#> 64 24.00 0 43 0 0
#> 95 24.00 0 68 0 1
#> 44 24.00 0 56 0 0
#> 121 24.00 0 57 1 0
#> 44.1 24.00 0 56 0 0
#> 196 24.00 0 19 0 0
#> 20 24.00 0 46 1 0
#> 53 24.00 0 32 0 1
#> 80 24.00 0 41 0 0
#> 31 24.00 0 36 0 1
#> 94 24.00 0 51 0 1
#> 200 24.00 0 64 0 0
#> 163 24.00 0 66 0 0
#> 186 24.00 0 45 1 0
#> 137 24.00 0 45 1 0
#> 137.1 24.00 0 45 1 0
#> 121.1 24.00 0 57 1 0
#> 44.2 24.00 0 56 0 0
#> 162 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 2 24.00 0 9 0 0
#> 182 24.00 0 35 0 0
#> 142 24.00 0 53 0 0
#> 102 24.00 0 49 0 0
#> 156 24.00 0 50 1 0
#> 143 24.00 0 51 0 0
#> 152 24.00 0 36 0 1
#> 82 24.00 0 34 0 0
#> 3 24.00 0 31 1 0
#> 162.1 24.00 0 51 0 0
#> 142.1 24.00 0 53 0 0
#> 17.1 24.00 0 38 0 1
#> 47 24.00 0 38 0 1
#> 33 24.00 0 53 0 0
#> 31.1 24.00 0 36 0 1
#> 62 24.00 0 71 0 0
#> 191 24.00 0 60 0 1
#> 98 24.00 0 34 1 0
#> 156.1 24.00 0 50 1 0
#> 112 24.00 0 61 0 0
#> 54 24.00 0 53 1 0
#> 17.2 24.00 0 38 0 1
#> 87 24.00 0 27 0 0
#> 146 24.00 0 63 1 0
#> 126.1 24.00 0 48 0 0
#> 11 24.00 0 42 0 1
#> 35 24.00 0 51 0 0
#> 103 24.00 0 56 1 0
#> 122 24.00 0 66 0 0
#> 62.1 24.00 0 71 0 0
#> 144 24.00 0 28 0 1
#> 131 24.00 0 66 0 0
#> 38 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 144.1 24.00 0 28 0 1
#> 3.1 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 27 24.00 0 63 1 0
#> 84 24.00 0 39 0 1
#> 2.1 24.00 0 9 0 0
#> 146.1 24.00 0 63 1 0
#> 3.2 24.00 0 31 1 0
#> 156.2 24.00 0 50 1 0
#> 121.2 24.00 0 57 1 0
#> 186.1 24.00 0 45 1 0
#> 131.1 24.00 0 66 0 0
#> 200.1 24.00 0 64 0 0
#> 87.1 24.00 0 27 0 0
#> 182.1 24.00 0 35 0 0
#> 53.1 24.00 0 32 0 1
#> 152.1 24.00 0 36 0 1
#> 83 24.00 0 6 0 0
#> 1 24.00 0 23 1 0
#> 72.1 24.00 0 40 0 1
#> 191.1 24.00 0 60 0 1
#> 53.2 24.00 0 32 0 1
#> 163.1 24.00 0 66 0 0
#> 27.1 24.00 0 63 1 0
#> 95.1 24.00 0 68 0 1
#> 104 24.00 0 50 1 0
#> 65 24.00 0 57 1 0
#> 80.1 24.00 0 41 0 0
#> 9 24.00 0 31 1 0
#> 144.2 24.00 0 28 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.954 NA NA NA
#> 2 age, Cure model 0.0141 NA NA NA
#> 3 grade_ii, Cure model 0.240 NA NA NA
#> 4 grade_iii, Cure model 1.07 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00431 NA NA NA
#> 2 grade_ii, Survival model 0.921 NA NA NA
#> 3 grade_iii, Survival model 0.436 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.95404 0.01414 0.24047 1.06604
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 251.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.95404430 0.01413929 0.24047235 1.06603712
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004314454 0.920662002 0.436228832
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.759848176 0.719119907 0.555354181 0.452740657 0.926096383 0.432664273
#> [7] 0.293885000 0.694269599 0.948749572 0.363377443 0.902962307 0.100129590
#> [13] 0.083625011 0.178348305 0.138053739 0.007376139 0.293885000 0.422568065
#> [19] 0.768023170 0.933760059 0.608972581 0.768023170 0.100129590 0.178348305
#> [25] 0.260785028 0.363377443 0.462823206 0.065768144 0.992791355 0.500540224
#> [31] 0.591237514 0.978292500 0.669228751 0.895165732 0.871704794 0.635279955
#> [37] 0.800137560 0.100129590 0.202269647 0.816133045 0.481768585 0.323698544
#> [43] 0.970945980 0.735497587 0.024584014 0.138053739 0.887353098 0.735497587
#> [49] 0.462823206 0.412511688 0.902962307 0.963533407 0.626567348 0.537196681
#> [55] 0.824177225 0.735497587 0.985573077 0.402413826 0.792116549 0.024584014
#> [61] 0.710860736 0.800137560 0.727348965 0.537196681 0.832147763 0.024584014
#> [67] 0.226682741 0.573378925 0.856101757 0.879524198 0.165396952 0.555354181
#> [73] 0.343580938 0.840139463 0.768023170 0.226682741 0.500540224 0.491140841
#> [79] 0.500540224 0.333614122 0.635279955 0.608972581 0.226682741 0.363377443
#> [85] 0.652472683 0.573378925 0.685872989 0.293885000 0.353453258 0.202269647
#> [91] 0.933760059 0.283263083 0.527957096 0.856101757 0.363377443 0.694269599
#> [97] 0.848112045 0.948749572 0.272235810 0.669228751 0.591237514 0.432664273
#> [103] 0.918402046 0.652472683 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 96 39 45 108 101 8 36 26 183 105 61 92 69
#> 14.54 15.59 17.42 18.29 9.97 18.43 21.19 15.77 9.24 19.75 10.12 22.92 23.23
#> 194 113 78 99 179 13 187 181 13.1 92.1 194.1 197 105.1
#> 22.40 22.86 23.88 21.19 18.63 14.34 9.92 16.46 14.34 22.92 22.40 21.60 19.75
#> 40 164 127 110 130 70 188 93 159 5 155 92.2 175
#> 18.00 23.60 3.53 17.56 16.47 7.38 16.16 10.33 10.55 16.43 13.08 22.92 21.91
#> 14 134 190 149 133 168 113.1 52 133.1 40.1 97 61.1 16
#> 12.89 17.81 20.81 8.37 14.65 23.72 22.86 10.42 14.65 18.00 19.14 10.12 8.71
#> 192 111 140 133.2 25 55 60 168.1 125 155.1 29 111.1 177
#> 16.44 17.45 12.68 14.65 6.32 19.34 13.15 23.72 15.65 13.08 15.45 17.45 12.53
#> 168.2 136 171 49 10 63 45.1 128 42 13.2 136.1 110.1 184
#> 23.72 21.83 16.57 12.19 10.53 22.77 17.42 20.35 12.43 14.34 21.83 17.56 17.77
#> 110.2 68 5.1 181.1 136.2 105.2 79 171.1 100 99.1 166 175.1 187.1
#> 17.56 20.62 16.43 16.46 21.83 19.75 16.23 16.57 16.07 21.19 19.98 21.91 9.92
#> 153 117 49.1 105.3 26.1 56 183.1 139 188.1 130.1 8.1 145 79.1
#> 21.33 17.46 12.19 19.75 15.77 12.21 9.24 21.49 16.16 16.47 18.43 10.07 16.23
#> 172 72 17 120 64 95 44 121 44.1 196 20 53 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 94 200 163 186 137 137.1 121.1 44.2 162 126 2 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 102 156 143 152 82 3 162.1 142.1 17.1 47 33 31.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 191 98 156.1 112 54 17.2 87 146 126.1 11 35 103
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 62.1 144 131 38 67 144.1 3.1 27 84 2.1 146.1 3.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156.2 121.2 186.1 131.1 200.1 87.1 182.1 53.1 152.1 83 1 72.1 191.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53.2 163.1 27.1 95.1 104 65 80.1 9 144.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[56]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.008803032 0.394562453 0.615884554
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.98375107 0.01568841 0.31096090
#> grade_iii, Cure model
#> 0.90044440
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 177 12.53 1 75 0 0
#> 45 17.42 1 54 0 1
#> 91 5.33 1 61 0 1
#> 91.1 5.33 1 61 0 1
#> 60 13.15 1 38 1 0
#> 192 16.44 1 31 1 0
#> 150 20.33 1 48 0 0
#> 10 10.53 1 34 0 0
#> 106 16.67 1 49 1 0
#> 110 17.56 1 65 0 1
#> 106.1 16.67 1 49 1 0
#> 40 18.00 1 28 1 0
#> 134 17.81 1 47 1 0
#> 14 12.89 1 21 0 0
#> 36 21.19 1 48 0 1
#> 29 15.45 1 68 1 0
#> 32 20.90 1 37 1 0
#> 139 21.49 1 63 1 0
#> 184 17.77 1 38 0 0
#> 153 21.33 1 55 1 0
#> 175 21.91 1 43 0 0
#> 140 12.68 1 59 1 0
#> 168 23.72 1 70 0 0
#> 189 10.51 1 NA 1 0
#> 42 12.43 1 49 0 1
#> 197 21.60 1 69 1 0
#> 184.1 17.77 1 38 0 0
#> 123 13.00 1 44 1 0
#> 157 15.10 1 47 0 0
#> 164 23.60 1 76 0 1
#> 5 16.43 1 51 0 1
#> 168.1 23.72 1 70 0 0
#> 169 22.41 1 46 0 0
#> 179 18.63 1 42 0 0
#> 43 12.10 1 61 0 1
#> 105 19.75 1 60 0 0
#> 78 23.88 1 43 0 0
#> 150.1 20.33 1 48 0 0
#> 90 20.94 1 50 0 1
#> 164.1 23.60 1 76 0 1
#> 113 22.86 1 34 0 0
#> 129 23.41 1 53 1 0
#> 96 14.54 1 33 0 1
#> 68 20.62 1 44 0 0
#> 136 21.83 1 43 0 1
#> 181 16.46 1 45 0 1
#> 36.1 21.19 1 48 0 1
#> 199 19.81 1 NA 0 1
#> 199.1 19.81 1 NA 0 1
#> 107 11.18 1 54 1 0
#> 40.1 18.00 1 28 1 0
#> 30 17.43 1 78 0 0
#> 79 16.23 1 54 1 0
#> 77 7.27 1 67 0 1
#> 179.1 18.63 1 42 0 0
#> 42.1 12.43 1 49 0 1
#> 189.1 10.51 1 NA 1 0
#> 175.1 21.91 1 43 0 0
#> 4 17.64 1 NA 0 1
#> 59 10.16 1 NA 1 0
#> 57 14.46 1 45 0 1
#> 4.1 17.64 1 NA 0 1
#> 130 16.47 1 53 0 1
#> 170 19.54 1 43 0 1
#> 77.1 7.27 1 67 0 1
#> 117 17.46 1 26 0 1
#> 180 14.82 1 37 0 0
#> 16 8.71 1 71 0 1
#> 13 14.34 1 54 0 1
#> 10.1 10.53 1 34 0 0
#> 123.1 13.00 1 44 1 0
#> 10.2 10.53 1 34 0 0
#> 51 18.23 1 83 0 1
#> 25 6.32 1 34 1 0
#> 63 22.77 1 31 1 0
#> 37 12.52 1 57 1 0
#> 181.1 16.46 1 45 0 1
#> 13.1 14.34 1 54 0 1
#> 189.2 10.51 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 14.1 12.89 1 21 0 0
#> 41 18.02 1 40 1 0
#> 194 22.40 1 38 0 1
#> 169.1 22.41 1 46 0 0
#> 105.1 19.75 1 60 0 0
#> 32.1 20.90 1 37 1 0
#> 150.2 20.33 1 48 0 0
#> 110.1 17.56 1 65 0 1
#> 199.2 19.81 1 NA 0 1
#> 190 20.81 1 42 1 0
#> 127 3.53 1 62 0 1
#> 110.2 17.56 1 65 0 1
#> 181.2 16.46 1 45 0 1
#> 133 14.65 1 57 0 0
#> 197.1 21.60 1 69 1 0
#> 106.2 16.67 1 49 1 0
#> 150.3 20.33 1 48 0 0
#> 14.2 12.89 1 21 0 0
#> 37.1 12.52 1 57 1 0
#> 136.1 21.83 1 43 0 1
#> 76 19.22 1 54 0 1
#> 158 20.14 1 74 1 0
#> 127.1 3.53 1 62 0 1
#> 127.2 3.53 1 62 0 1
#> 189.3 10.51 1 NA 1 0
#> 49 12.19 1 48 1 0
#> 93 10.33 1 52 0 1
#> 124 9.73 1 NA 1 0
#> 16.1 8.71 1 71 0 1
#> 97 19.14 1 65 0 1
#> 189.4 10.51 1 NA 1 0
#> 130.1 16.47 1 53 0 1
#> 126 24.00 0 48 0 0
#> 3 24.00 0 31 1 0
#> 148 24.00 0 61 1 0
#> 152 24.00 0 36 0 1
#> 131 24.00 0 66 0 0
#> 152.1 24.00 0 36 0 1
#> 47 24.00 0 38 0 1
#> 138 24.00 0 44 1 0
#> 191 24.00 0 60 0 1
#> 102 24.00 0 49 0 0
#> 120 24.00 0 68 0 1
#> 143 24.00 0 51 0 0
#> 118 24.00 0 44 1 0
#> 182 24.00 0 35 0 0
#> 31 24.00 0 36 0 1
#> 64 24.00 0 43 0 0
#> 135 24.00 0 58 1 0
#> 33 24.00 0 53 0 0
#> 82 24.00 0 34 0 0
#> 17 24.00 0 38 0 1
#> 143.1 24.00 0 51 0 0
#> 151 24.00 0 42 0 0
#> 17.1 24.00 0 38 0 1
#> 20 24.00 0 46 1 0
#> 174 24.00 0 49 1 0
#> 31.1 24.00 0 36 0 1
#> 126.1 24.00 0 48 0 0
#> 2 24.00 0 9 0 0
#> 142 24.00 0 53 0 0
#> 35 24.00 0 51 0 0
#> 33.1 24.00 0 53 0 0
#> 82.1 24.00 0 34 0 0
#> 20.1 24.00 0 46 1 0
#> 33.2 24.00 0 53 0 0
#> 48 24.00 0 31 1 0
#> 174.1 24.00 0 49 1 0
#> 12 24.00 0 63 0 0
#> 109 24.00 0 48 0 0
#> 161 24.00 0 45 0 0
#> 54 24.00 0 53 1 0
#> 47.1 24.00 0 38 0 1
#> 94 24.00 0 51 0 1
#> 104 24.00 0 50 1 0
#> 126.2 24.00 0 48 0 0
#> 151.1 24.00 0 42 0 0
#> 193 24.00 0 45 0 1
#> 80 24.00 0 41 0 0
#> 156 24.00 0 50 1 0
#> 7 24.00 0 37 1 0
#> 82.2 24.00 0 34 0 0
#> 186 24.00 0 45 1 0
#> 132 24.00 0 55 0 0
#> 2.1 24.00 0 9 0 0
#> 44 24.00 0 56 0 0
#> 131.1 24.00 0 66 0 0
#> 20.2 24.00 0 46 1 0
#> 64.1 24.00 0 43 0 0
#> 11 24.00 0 42 0 1
#> 198 24.00 0 66 0 1
#> 95 24.00 0 68 0 1
#> 27 24.00 0 63 1 0
#> 33.3 24.00 0 53 0 0
#> 44.1 24.00 0 56 0 0
#> 12.1 24.00 0 63 0 0
#> 87 24.00 0 27 0 0
#> 102.1 24.00 0 49 0 0
#> 146 24.00 0 63 1 0
#> 28 24.00 0 67 1 0
#> 148.1 24.00 0 61 1 0
#> 73 24.00 0 NA 0 1
#> 143.2 24.00 0 51 0 0
#> 11.1 24.00 0 42 0 1
#> 34 24.00 0 36 0 0
#> 191.1 24.00 0 60 0 1
#> 1 24.00 0 23 1 0
#> 115 24.00 0 NA 1 0
#> 182.1 24.00 0 35 0 0
#> 141 24.00 0 44 1 0
#> 1.1 24.00 0 23 1 0
#> 65 24.00 0 57 1 0
#> 163 24.00 0 66 0 0
#> 191.2 24.00 0 60 0 1
#> 162 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 161.1 24.00 0 45 0 0
#> 3.1 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 198.1 24.00 0 66 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.984 NA NA NA
#> 2 age, Cure model 0.0157 NA NA NA
#> 3 grade_ii, Cure model 0.311 NA NA NA
#> 4 grade_iii, Cure model 0.900 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00880 NA NA NA
#> 2 grade_ii, Survival model 0.395 NA NA NA
#> 3 grade_iii, Survival model 0.616 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.98375 0.01569 0.31096 0.90044
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.8
#> Residual Deviance: 247.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.98375107 0.01568841 0.31096090 0.90044440
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.008803032 0.394562453 0.615884554
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.769702729 0.480654257 0.947917221 0.947917221 0.697461819 0.573136168
#> [7] 0.234774842 0.853447788 0.491166362 0.428765610 0.491166362 0.376773668
#> [13] 0.397386096 0.728398282 0.168565003 0.614219427 0.197043763 0.148687867
#> [19] 0.407834771 0.158599653 0.091937588 0.759257046 0.006789924 0.801161994
#> [25] 0.129706087 0.407834771 0.707825991 0.624574982 0.021087650 0.583406695
#> [31] 0.006789924 0.063749253 0.334935853 0.832483959 0.283229765 0.001576650
#> [37] 0.234774842 0.187447274 0.021087650 0.045273198 0.036413453 0.655979902
#> [43] 0.225144553 0.111246054 0.542804392 0.168565003 0.842960814 0.376773668
#> [49] 0.470107361 0.593644484 0.916384009 0.334935853 0.801161994 0.091937588
#> [55] 0.666444410 0.522103380 0.303857283 0.916384009 0.459676713 0.634989044
#> [61] 0.895380883 0.676868696 0.853447788 0.707825991 0.853447788 0.355671761
#> [67] 0.937374445 0.054610177 0.780217373 0.542804392 0.676868696 0.603896000
#> [73] 0.728398282 0.366229293 0.082391265 0.063749253 0.283229765 0.197043763
#> [79] 0.234774842 0.428765610 0.215644795 0.968847528 0.428765610 0.542804392
#> [85] 0.645450806 0.129706087 0.491166362 0.234774842 0.728398282 0.780217373
#> [91] 0.111246054 0.314256114 0.273031864 0.968847528 0.968847528 0.821996270
#> [97] 0.884819279 0.895380883 0.324603323 0.522103380 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 177 45 91 91.1 60 192 150 10 106 110 106.1 40 134
#> 12.53 17.42 5.33 5.33 13.15 16.44 20.33 10.53 16.67 17.56 16.67 18.00 17.81
#> 14 36 29 32 139 184 153 175 140 168 42 197 184.1
#> 12.89 21.19 15.45 20.90 21.49 17.77 21.33 21.91 12.68 23.72 12.43 21.60 17.77
#> 123 157 164 5 168.1 169 179 43 105 78 150.1 90 164.1
#> 13.00 15.10 23.60 16.43 23.72 22.41 18.63 12.10 19.75 23.88 20.33 20.94 23.60
#> 113 129 96 68 136 181 36.1 107 40.1 30 79 77 179.1
#> 22.86 23.41 14.54 20.62 21.83 16.46 21.19 11.18 18.00 17.43 16.23 7.27 18.63
#> 42.1 175.1 57 130 170 77.1 117 180 16 13 10.1 123.1 10.2
#> 12.43 21.91 14.46 16.47 19.54 7.27 17.46 14.82 8.71 14.34 10.53 13.00 10.53
#> 51 25 63 37 181.1 13.1 100 14.1 41 194 169.1 105.1 32.1
#> 18.23 6.32 22.77 12.52 16.46 14.34 16.07 12.89 18.02 22.40 22.41 19.75 20.90
#> 150.2 110.1 190 127 110.2 181.2 133 197.1 106.2 150.3 14.2 37.1 136.1
#> 20.33 17.56 20.81 3.53 17.56 16.46 14.65 21.60 16.67 20.33 12.89 12.52 21.83
#> 76 158 127.1 127.2 49 93 16.1 97 130.1 126 3 148 152
#> 19.22 20.14 3.53 3.53 12.19 10.33 8.71 19.14 16.47 24.00 24.00 24.00 24.00
#> 131 152.1 47 138 191 102 120 143 118 182 31 64 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 82 17 143.1 151 17.1 20 174 31.1 126.1 2 142 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33.1 82.1 20.1 33.2 48 174.1 12 109 161 54 47.1 94 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126.2 151.1 193 80 156 7 82.2 186 132 2.1 44 131.1 20.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64.1 11 198 95 27 33.3 44.1 12.1 87 102.1 146 28 148.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143.2 11.1 34 191.1 1 182.1 141 1.1 65 163 191.2 162 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161.1 3.1 98 198.1
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[57]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01072888 0.94043690 0.56635872
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.74667169 0.01151432 0.17327765
#> grade_iii, Cure model
#> 0.88549578
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 41 18.02 1 40 1 0
#> 179 18.63 1 42 0 0
#> 197 21.60 1 69 1 0
#> 79 16.23 1 54 1 0
#> 61 10.12 1 36 0 1
#> 183 9.24 1 67 1 0
#> 16 8.71 1 71 0 1
#> 168 23.72 1 70 0 0
#> 179.1 18.63 1 42 0 0
#> 177 12.53 1 75 0 0
#> 127 3.53 1 62 0 1
#> 52 10.42 1 52 0 1
#> 170 19.54 1 43 0 1
#> 158 20.14 1 74 1 0
#> 24 23.89 1 38 0 0
#> 159 10.55 1 50 0 1
#> 188 16.16 1 46 0 1
#> 180 14.82 1 37 0 0
#> 125 15.65 1 67 1 0
#> 88 18.37 1 47 0 0
#> 125.1 15.65 1 67 1 0
#> 158.1 20.14 1 74 1 0
#> 78 23.88 1 43 0 0
#> 175 21.91 1 43 0 0
#> 89 11.44 1 NA 0 0
#> 96 14.54 1 33 0 1
#> 153 21.33 1 55 1 0
#> 117 17.46 1 26 0 1
#> 89.1 11.44 1 NA 0 0
#> 199 19.81 1 NA 0 1
#> 37 12.52 1 57 1 0
#> 114 13.68 1 NA 0 0
#> 78.1 23.88 1 43 0 0
#> 179.2 18.63 1 42 0 0
#> 60 13.15 1 38 1 0
#> 105 19.75 1 60 0 0
#> 89.2 11.44 1 NA 0 0
#> 187 9.92 1 39 1 0
#> 106 16.67 1 49 1 0
#> 136 21.83 1 43 0 1
#> 114.1 13.68 1 NA 0 0
#> 189 10.51 1 NA 1 0
#> 6 15.64 1 39 0 0
#> 81 14.06 1 34 0 0
#> 14 12.89 1 21 0 0
#> 5 16.43 1 51 0 1
#> 194 22.40 1 38 0 1
#> 89.3 11.44 1 NA 0 0
#> 88.1 18.37 1 47 0 0
#> 158.2 20.14 1 74 1 0
#> 128 20.35 1 35 0 1
#> 29 15.45 1 68 1 0
#> 168.1 23.72 1 70 0 0
#> 199.1 19.81 1 NA 0 1
#> 61.1 10.12 1 36 0 1
#> 96.1 14.54 1 33 0 1
#> 36 21.19 1 48 0 1
#> 16.1 8.71 1 71 0 1
#> 69 23.23 1 25 0 1
#> 77 7.27 1 67 0 1
#> 42 12.43 1 49 0 1
#> 166 19.98 1 48 0 0
#> 134 17.81 1 47 1 0
#> 15 22.68 1 48 0 0
#> 188.1 16.16 1 46 0 1
#> 195 11.76 1 NA 1 0
#> 181 16.46 1 45 0 1
#> 114.2 13.68 1 NA 0 0
#> 110 17.56 1 65 0 1
#> 149 8.37 1 33 1 0
#> 158.3 20.14 1 74 1 0
#> 184 17.77 1 38 0 0
#> 77.1 7.27 1 67 0 1
#> 76 19.22 1 54 0 1
#> 51 18.23 1 83 0 1
#> 81.1 14.06 1 34 0 0
#> 129 23.41 1 53 1 0
#> 159.1 10.55 1 50 0 1
#> 57 14.46 1 45 0 1
#> 140 12.68 1 59 1 0
#> 100 16.07 1 60 0 0
#> 187.1 9.92 1 39 1 0
#> 25 6.32 1 34 1 0
#> 154 12.63 1 20 1 0
#> 5.1 16.43 1 51 0 1
#> 41.1 18.02 1 40 1 0
#> 8 18.43 1 32 0 0
#> 136.1 21.83 1 43 0 1
#> 150 20.33 1 48 0 0
#> 100.1 16.07 1 60 0 0
#> 10 10.53 1 34 0 0
#> 37.1 12.52 1 57 1 0
#> 86 23.81 1 58 0 1
#> 14.1 12.89 1 21 0 0
#> 167 15.55 1 56 1 0
#> 128.1 20.35 1 35 0 1
#> 50 10.02 1 NA 1 0
#> 123 13.00 1 44 1 0
#> 189.1 10.51 1 NA 1 0
#> 6.1 15.64 1 39 0 0
#> 130 16.47 1 53 0 1
#> 110.1 17.56 1 65 0 1
#> 108 18.29 1 39 0 1
#> 110.2 17.56 1 65 0 1
#> 107 11.18 1 54 1 0
#> 107.1 11.18 1 54 1 0
#> 145 10.07 1 65 1 0
#> 61.2 10.12 1 36 0 1
#> 166.1 19.98 1 48 0 0
#> 6.2 15.64 1 39 0 0
#> 78.2 23.88 1 43 0 0
#> 164 23.60 1 76 0 1
#> 35 24.00 0 51 0 0
#> 34 24.00 0 36 0 0
#> 64 24.00 0 43 0 0
#> 147 24.00 0 76 1 0
#> 126 24.00 0 48 0 0
#> 3 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 151 24.00 0 42 0 0
#> 193 24.00 0 45 0 1
#> 121 24.00 0 57 1 0
#> 84 24.00 0 39 0 1
#> 116 24.00 0 58 0 1
#> 163 24.00 0 66 0 0
#> 74 24.00 0 43 0 1
#> 115 24.00 0 NA 1 0
#> 137 24.00 0 45 1 0
#> 20 24.00 0 46 1 0
#> 163.1 24.00 0 66 0 0
#> 191 24.00 0 60 0 1
#> 3.1 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 165 24.00 0 47 0 0
#> 75 24.00 0 21 1 0
#> 3.2 24.00 0 31 1 0
#> 48 24.00 0 31 1 0
#> 38 24.00 0 31 1 0
#> 151.1 24.00 0 42 0 0
#> 46 24.00 0 71 0 0
#> 65 24.00 0 57 1 0
#> 34.1 24.00 0 36 0 0
#> 67 24.00 0 25 0 0
#> 104 24.00 0 50 1 0
#> 109 24.00 0 48 0 0
#> 71 24.00 0 51 0 0
#> 121.1 24.00 0 57 1 0
#> 31 24.00 0 36 0 1
#> 137.1 24.00 0 45 1 0
#> 120 24.00 0 68 0 1
#> 161 24.00 0 45 0 0
#> 185 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 173 24.00 0 19 0 1
#> 34.2 24.00 0 36 0 0
#> 198 24.00 0 66 0 1
#> 116.1 24.00 0 58 0 1
#> 38.1 24.00 0 31 1 0
#> 46.1 24.00 0 71 0 0
#> 28 24.00 0 67 1 0
#> 28.1 24.00 0 67 1 0
#> 137.2 24.00 0 45 1 0
#> 64.1 24.00 0 43 0 0
#> 162 24.00 0 51 0 0
#> 200 24.00 0 64 0 0
#> 102 24.00 0 49 0 0
#> 54 24.00 0 53 1 0
#> 104.1 24.00 0 50 1 0
#> 142 24.00 0 53 0 0
#> 44 24.00 0 56 0 0
#> 191.1 24.00 0 60 0 1
#> 3.3 24.00 0 31 1 0
#> 3.4 24.00 0 31 1 0
#> 33 24.00 0 53 0 0
#> 119 24.00 0 17 0 0
#> 82 24.00 0 34 0 0
#> 7.1 24.00 0 37 1 0
#> 48.1 24.00 0 31 1 0
#> 173.1 24.00 0 19 0 1
#> 191.2 24.00 0 60 0 1
#> 193.1 24.00 0 45 0 1
#> 200.1 24.00 0 64 0 0
#> 109.1 24.00 0 48 0 0
#> 131 24.00 0 66 0 0
#> 163.2 24.00 0 66 0 0
#> 27 24.00 0 63 1 0
#> 44.1 24.00 0 56 0 0
#> 71.1 24.00 0 51 0 0
#> 135 24.00 0 58 1 0
#> 47.1 24.00 0 38 0 1
#> 94 24.00 0 51 0 1
#> 7.2 24.00 0 37 1 0
#> 147.1 24.00 0 76 1 0
#> 35.1 24.00 0 51 0 0
#> 172 24.00 0 41 0 0
#> 87 24.00 0 27 0 0
#> 172.1 24.00 0 41 0 0
#> 131.1 24.00 0 66 0 0
#> 31.1 24.00 0 36 0 1
#> 151.2 24.00 0 42 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.747 NA NA NA
#> 2 age, Cure model 0.0115 NA NA NA
#> 3 grade_ii, Cure model 0.173 NA NA NA
#> 4 grade_iii, Cure model 0.885 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0107 NA NA NA
#> 2 grade_ii, Survival model 0.940 NA NA NA
#> 3 grade_iii, Survival model 0.566 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.74667 0.01151 0.17328 0.88550
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 257.1
#> Residual Deviance: 249.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.74667169 0.01151432 0.17327765 0.88549578
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01072888 0.94043690 0.56635872
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.377353252 0.291725823 0.142660300 0.513492892 0.862999527 0.922110873
#> [7] 0.931895009 0.035608070 0.291725823 0.762401124 0.990299671 0.852936505
#> [13] 0.271120363 0.203871595 0.001840789 0.822936904 0.523844996 0.637921004
#> [19] 0.565094624 0.333496149 0.565094624 0.203871595 0.008277547 0.110647874
#> [25] 0.648450164 0.153328836 0.450809125 0.772661419 0.008277547 0.291725823
#> [31] 0.700510435 0.260776628 0.902595322 0.461408771 0.121789530 0.585716647
#> [37] 0.679611749 0.721256619 0.492817990 0.099906493 0.333496149 0.203871595
#> [43] 0.174027205 0.627448481 0.035608070 0.862999527 0.648450164 0.163695151
#> [49] 0.931895009 0.078538918 0.961172513 0.792838509 0.240866776 0.398398490
#> [55] 0.088964192 0.523844996 0.482361260 0.419512835 0.951433004 0.203871595
#> [61] 0.408910029 0.961172513 0.281420636 0.366261067 0.679611749 0.067612918
#> [67] 0.822936904 0.669179655 0.741882847 0.544284311 0.902595322 0.980608276
#> [73] 0.752216592 0.492817990 0.377353252 0.322713688 0.121789530 0.193606515
#> [79] 0.544284311 0.842872475 0.772661419 0.026763261 0.721256619 0.616934768
#> [85] 0.174027205 0.710928732 0.585716647 0.471884747 0.419512835 0.355261129
#> [91] 0.419512835 0.802986681 0.802986681 0.892635831 0.862999527 0.240866776
#> [97] 0.585716647 0.008277547 0.055836469 0.000000000 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 41 179 197 79 61 183 16 168 179.1 177 127 52 170
#> 18.02 18.63 21.60 16.23 10.12 9.24 8.71 23.72 18.63 12.53 3.53 10.42 19.54
#> 158 24 159 188 180 125 88 125.1 158.1 78 175 96 153
#> 20.14 23.89 10.55 16.16 14.82 15.65 18.37 15.65 20.14 23.88 21.91 14.54 21.33
#> 117 37 78.1 179.2 60 105 187 106 136 6 81 14 5
#> 17.46 12.52 23.88 18.63 13.15 19.75 9.92 16.67 21.83 15.64 14.06 12.89 16.43
#> 194 88.1 158.2 128 29 168.1 61.1 96.1 36 16.1 69 77 42
#> 22.40 18.37 20.14 20.35 15.45 23.72 10.12 14.54 21.19 8.71 23.23 7.27 12.43
#> 166 134 15 188.1 181 110 149 158.3 184 77.1 76 51 81.1
#> 19.98 17.81 22.68 16.16 16.46 17.56 8.37 20.14 17.77 7.27 19.22 18.23 14.06
#> 129 159.1 57 140 100 187.1 25 154 5.1 41.1 8 136.1 150
#> 23.41 10.55 14.46 12.68 16.07 9.92 6.32 12.63 16.43 18.02 18.43 21.83 20.33
#> 100.1 10 37.1 86 14.1 167 128.1 123 6.1 130 110.1 108 110.2
#> 16.07 10.53 12.52 23.81 12.89 15.55 20.35 13.00 15.64 16.47 17.56 18.29 17.56
#> 107 107.1 145 61.2 166.1 6.2 78.2 164 35 34 64 147 126
#> 11.18 11.18 10.07 10.12 19.98 15.64 23.88 23.60 24.00 24.00 24.00 24.00 24.00
#> 3 152 151 193 121 84 116 163 74 137 20 163.1 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.1 47 165 75 3.2 48 38 151.1 46 65 34.1 67 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109 71 121.1 31 137.1 120 161 185 7 173 34.2 198 116.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38.1 46.1 28 28.1 137.2 64.1 162 200 102 54 104.1 142 44
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191.1 3.3 3.4 33 119 82 7.1 48.1 173.1 191.2 193.1 200.1 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 163.2 27 44.1 71.1 135 47.1 94 7.2 147.1 35.1 172 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.1 131.1 31.1 151.2
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[58]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01305735 0.96572873 0.35128854
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.48693680 0.01489238 -0.31410211
#> grade_iii, Cure model
#> 0.25164245
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 57 14.46 1 45 0 1
#> 159 10.55 1 50 0 1
#> 140 12.68 1 59 1 0
#> 15 22.68 1 48 0 0
#> 86 23.81 1 58 0 1
#> 89 11.44 1 NA 0 0
#> 15.1 22.68 1 48 0 0
#> 164 23.60 1 76 0 1
#> 52 10.42 1 52 0 1
#> 92 22.92 1 47 0 1
#> 85 16.44 1 36 0 0
#> 79 16.23 1 54 1 0
#> 150 20.33 1 48 0 0
#> 145 10.07 1 65 1 0
#> 23 16.92 1 61 0 0
#> 127 3.53 1 62 0 1
#> 29 15.45 1 68 1 0
#> 169 22.41 1 46 0 0
#> 39 15.59 1 37 0 1
#> 167 15.55 1 56 1 0
#> 157 15.10 1 47 0 0
#> 60 13.15 1 38 1 0
#> 30 17.43 1 78 0 0
#> 69 23.23 1 25 0 1
#> 194 22.40 1 38 0 1
#> 52.1 10.42 1 52 0 1
#> 113 22.86 1 34 0 0
#> 92.1 22.92 1 47 0 1
#> 197 21.60 1 69 1 0
#> 145.1 10.07 1 65 1 0
#> 89.1 11.44 1 NA 0 0
#> 140.1 12.68 1 59 1 0
#> 170 19.54 1 43 0 1
#> 89.2 11.44 1 NA 0 0
#> 78 23.88 1 43 0 0
#> 26 15.77 1 49 0 1
#> 56 12.21 1 60 0 0
#> 42 12.43 1 49 0 1
#> 197.1 21.60 1 69 1 0
#> 51 18.23 1 83 0 1
#> 59 10.16 1 NA 1 0
#> 184 17.77 1 38 0 0
#> 123 13.00 1 44 1 0
#> 5 16.43 1 51 0 1
#> 125 15.65 1 67 1 0
#> 175 21.91 1 43 0 0
#> 155 13.08 1 26 0 0
#> 76 19.22 1 54 0 1
#> 101 9.97 1 10 0 1
#> 93 10.33 1 52 0 1
#> 55 19.34 1 69 0 1
#> 81 14.06 1 34 0 0
#> 25 6.32 1 34 1 0
#> 150.1 20.33 1 48 0 0
#> 188 16.16 1 46 0 1
#> 123.1 13.00 1 44 1 0
#> 61 10.12 1 36 0 1
#> 136 21.83 1 43 0 1
#> 100 16.07 1 60 0 0
#> 6 15.64 1 39 0 0
#> 128 20.35 1 35 0 1
#> 25.1 6.32 1 34 1 0
#> 197.2 21.60 1 69 1 0
#> 180 14.82 1 37 0 0
#> 183 9.24 1 67 1 0
#> 101.1 9.97 1 10 0 1
#> 169.1 22.41 1 46 0 0
#> 16 8.71 1 71 0 1
#> 187 9.92 1 39 1 0
#> 8 18.43 1 32 0 0
#> 181 16.46 1 45 0 1
#> 145.2 10.07 1 65 1 0
#> 52.2 10.42 1 52 0 1
#> 61.1 10.12 1 36 0 1
#> 155.1 13.08 1 26 0 0
#> 134 17.81 1 47 1 0
#> 134.1 17.81 1 47 1 0
#> 68 20.62 1 44 0 0
#> 134.2 17.81 1 47 1 0
#> 155.2 13.08 1 26 0 0
#> 56.1 12.21 1 60 0 0
#> 5.1 16.43 1 51 0 1
#> 88 18.37 1 47 0 0
#> 96 14.54 1 33 0 1
#> 167.1 15.55 1 56 1 0
#> 13 14.34 1 54 0 1
#> 184.1 17.77 1 38 0 0
#> 140.2 12.68 1 59 1 0
#> 59.1 10.16 1 NA 1 0
#> 52.3 10.42 1 52 0 1
#> 60.1 13.15 1 38 1 0
#> 15.2 22.68 1 48 0 0
#> 125.1 15.65 1 67 1 0
#> 180.1 14.82 1 37 0 0
#> 60.2 13.15 1 38 1 0
#> 110 17.56 1 65 0 1
#> 108 18.29 1 39 0 1
#> 124 9.73 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 159.1 10.55 1 50 0 1
#> 187.1 9.92 1 39 1 0
#> 140.3 12.68 1 59 1 0
#> 114 13.68 1 NA 0 0
#> 187.2 9.92 1 39 1 0
#> 51.1 18.23 1 83 0 1
#> 153 21.33 1 55 1 0
#> 169.2 22.41 1 46 0 0
#> 106 16.67 1 49 1 0
#> 97 19.14 1 65 0 1
#> 85.1 16.44 1 36 0 0
#> 32 20.90 1 37 1 0
#> 189 10.51 1 NA 1 0
#> 2 24.00 0 9 0 0
#> 135 24.00 0 58 1 0
#> 33 24.00 0 53 0 0
#> 115 24.00 0 NA 1 0
#> 38 24.00 0 31 1 0
#> 102 24.00 0 49 0 0
#> 121 24.00 0 57 1 0
#> 119 24.00 0 17 0 0
#> 17 24.00 0 38 0 1
#> 104 24.00 0 50 1 0
#> 118 24.00 0 44 1 0
#> 141 24.00 0 44 1 0
#> 118.1 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 182 24.00 0 35 0 0
#> 103 24.00 0 56 1 0
#> 103.1 24.00 0 56 1 0
#> 147 24.00 0 76 1 0
#> 161 24.00 0 45 0 0
#> 7 24.00 0 37 1 0
#> 7.1 24.00 0 37 1 0
#> 62 24.00 0 71 0 0
#> 54 24.00 0 53 1 0
#> 156 24.00 0 50 1 0
#> 126 24.00 0 48 0 0
#> 116 24.00 0 58 0 1
#> 103.2 24.00 0 56 1 0
#> 135.1 24.00 0 58 1 0
#> 138 24.00 0 44 1 0
#> 121.1 24.00 0 57 1 0
#> 35 24.00 0 51 0 0
#> 116.1 24.00 0 58 0 1
#> 143 24.00 0 51 0 0
#> 132 24.00 0 55 0 0
#> 3 24.00 0 31 1 0
#> 94 24.00 0 51 0 1
#> 2.1 24.00 0 9 0 0
#> 172 24.00 0 41 0 0
#> 147.1 24.00 0 76 1 0
#> 74 24.00 0 43 0 1
#> 95 24.00 0 68 0 1
#> 11 24.00 0 42 0 1
#> 17.1 24.00 0 38 0 1
#> 104.1 24.00 0 50 1 0
#> 104.2 24.00 0 50 1 0
#> 53 24.00 0 32 0 1
#> 83 24.00 0 6 0 0
#> 74.1 24.00 0 43 0 1
#> 162 24.00 0 51 0 0
#> 191 24.00 0 60 0 1
#> 198 24.00 0 66 0 1
#> 62.1 24.00 0 71 0 0
#> 95.1 24.00 0 68 0 1
#> 200 24.00 0 64 0 0
#> 162.1 24.00 0 51 0 0
#> 27 24.00 0 63 1 0
#> 75 24.00 0 21 1 0
#> 185 24.00 0 44 1 0
#> 27.1 24.00 0 63 1 0
#> 75.1 24.00 0 21 1 0
#> 173 24.00 0 19 0 1
#> 47 24.00 0 38 0 1
#> 33.1 24.00 0 53 0 0
#> 137 24.00 0 45 1 0
#> 73 24.00 0 NA 0 1
#> 185.1 24.00 0 44 1 0
#> 19 24.00 0 57 0 1
#> 3.1 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 74.2 24.00 0 43 0 1
#> 1 24.00 0 23 1 0
#> 54.1 24.00 0 53 1 0
#> 165 24.00 0 47 0 0
#> 47.1 24.00 0 38 0 1
#> 80 24.00 0 41 0 0
#> 72 24.00 0 40 0 1
#> 144 24.00 0 28 0 1
#> 103.3 24.00 0 56 1 0
#> 19.1 24.00 0 57 0 1
#> 98 24.00 0 34 1 0
#> 152 24.00 0 36 0 1
#> 112 24.00 0 61 0 0
#> 160 24.00 0 31 1 0
#> 35.1 24.00 0 51 0 0
#> 17.2 24.00 0 38 0 1
#> 151 24.00 0 42 0 0
#> 31 24.00 0 36 0 1
#> 12 24.00 0 63 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.487 NA NA NA
#> 2 age, Cure model 0.0149 NA NA NA
#> 3 grade_ii, Cure model -0.314 NA NA NA
#> 4 grade_iii, Cure model 0.252 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0131 NA NA NA
#> 2 grade_ii, Survival model 0.966 NA NA NA
#> 3 grade_iii, Survival model 0.351 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.48694 0.01489 -0.31410 0.25164
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 257.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.48693680 0.01489238 -0.31410211 0.25164245
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01305735 0.96572873 0.35128854
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.565604180 0.759666747 0.685387150 0.031120402 0.002829336 0.031120402
#> [7] 0.006351391 0.781495476 0.016028587 0.361666666 0.403477272 0.152854169
#> [13] 0.858723268 0.320696580 0.989217084 0.510956990 0.049125889 0.478638523
#> [19] 0.489575955 0.521743295 0.599172713 0.310600441 0.011198331 0.070774002
#> [25] 0.781495476 0.025446887 0.016028587 0.096426428 0.858723268 0.685387150
#> [31] 0.169731605 0.000490074 0.435507208 0.738000139 0.727258719 0.096426428
#> [37] 0.234234571 0.281497103 0.663833357 0.382417625 0.446369375 0.079012070
#> [43] 0.631264593 0.187405191 0.891811113 0.825216586 0.178475875 0.587910563
#> [49] 0.967853931 0.152854169 0.414064852 0.663833357 0.836413282 0.087636973
#> [55] 0.424712529 0.467731884 0.144606029 0.967853931 0.096426428 0.532632859
#> [61] 0.946094069 0.891811113 0.049125889 0.956946926 0.913872798 0.205687887
#> [67] 0.351363070 0.858723268 0.781495476 0.836413282 0.631264593 0.253899769
#> [73] 0.253899769 0.136404932 0.253899769 0.631264593 0.738000139 0.382417625
#> [79] 0.215056140 0.554528961 0.489575955 0.576725232 0.281497103 0.685387150
#> [85] 0.781495476 0.599172713 0.031120402 0.446369375 0.532632859 0.599172713
#> [91] 0.300709704 0.224615423 0.341122689 0.759666747 0.913872798 0.685387150
#> [97] 0.913872798 0.234234571 0.120102286 0.049125889 0.330970330 0.196463173
#> [103] 0.361666666 0.128413882 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 57 159 140 15 86 15.1 164 52 92 85 79 150 145
#> 14.46 10.55 12.68 22.68 23.81 22.68 23.60 10.42 22.92 16.44 16.23 20.33 10.07
#> 23 127 29 169 39 167 157 60 30 69 194 52.1 113
#> 16.92 3.53 15.45 22.41 15.59 15.55 15.10 13.15 17.43 23.23 22.40 10.42 22.86
#> 92.1 197 145.1 140.1 170 78 26 56 42 197.1 51 184 123
#> 22.92 21.60 10.07 12.68 19.54 23.88 15.77 12.21 12.43 21.60 18.23 17.77 13.00
#> 5 125 175 155 76 101 93 55 81 25 150.1 188 123.1
#> 16.43 15.65 21.91 13.08 19.22 9.97 10.33 19.34 14.06 6.32 20.33 16.16 13.00
#> 61 136 100 6 128 25.1 197.2 180 183 101.1 169.1 16 187
#> 10.12 21.83 16.07 15.64 20.35 6.32 21.60 14.82 9.24 9.97 22.41 8.71 9.92
#> 8 181 145.2 52.2 61.1 155.1 134 134.1 68 134.2 155.2 56.1 5.1
#> 18.43 16.46 10.07 10.42 10.12 13.08 17.81 17.81 20.62 17.81 13.08 12.21 16.43
#> 88 96 167.1 13 184.1 140.2 52.3 60.1 15.2 125.1 180.1 60.2 110
#> 18.37 14.54 15.55 14.34 17.77 12.68 10.42 13.15 22.68 15.65 14.82 13.15 17.56
#> 108 130 159.1 187.1 140.3 187.2 51.1 153 169.2 106 97 85.1 32
#> 18.29 16.47 10.55 9.92 12.68 9.92 18.23 21.33 22.41 16.67 19.14 16.44 20.90
#> 2 135 33 38 102 121 119 17 104 118 141 118.1 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 103 103.1 147 161 7 7.1 62 54 156 126 116 103.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135.1 138 121.1 35 116.1 143 132 3 94 2.1 172 147.1 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 11 17.1 104.1 104.2 53 83 74.1 162 191 198 62.1 95.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 162.1 27 75 185 27.1 75.1 173 47 33.1 137 185.1 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.1 109 74.2 1 54.1 165 47.1 80 72 144 103.3 19.1 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 112 160 35.1 17.2 151 31 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[59]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.008872266 0.255888626 0.470015041
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.315478330 0.002748941 0.361081153
#> grade_iii, Cure model
#> 0.703483987
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 190 20.81 1 42 1 0
#> 6 15.64 1 39 0 0
#> 16 8.71 1 71 0 1
#> 113 22.86 1 34 0 0
#> 190.1 20.81 1 42 1 0
#> 81 14.06 1 34 0 0
#> 29 15.45 1 68 1 0
#> 155 13.08 1 26 0 0
#> 100 16.07 1 60 0 0
#> 97 19.14 1 65 0 1
#> 181 16.46 1 45 0 1
#> 50 10.02 1 NA 1 0
#> 145 10.07 1 65 1 0
#> 57 14.46 1 45 0 1
#> 189 10.51 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 164 23.60 1 76 0 1
#> 99 21.19 1 38 0 1
#> 108 18.29 1 39 0 1
#> 78.1 23.88 1 43 0 0
#> 106 16.67 1 49 1 0
#> 52 10.42 1 52 0 1
#> 183 9.24 1 67 1 0
#> 114 13.68 1 NA 0 0
#> 128 20.35 1 35 0 1
#> 14 12.89 1 21 0 0
#> 133 14.65 1 57 0 0
#> 155.1 13.08 1 26 0 0
#> 124 9.73 1 NA 1 0
#> 63 22.77 1 31 1 0
#> 190.2 20.81 1 42 1 0
#> 153 21.33 1 55 1 0
#> 77 7.27 1 67 0 1
#> 194 22.40 1 38 0 1
#> 157 15.10 1 47 0 0
#> 153.1 21.33 1 55 1 0
#> 149 8.37 1 33 1 0
#> 16.1 8.71 1 71 0 1
#> 190.3 20.81 1 42 1 0
#> 159 10.55 1 50 0 1
#> 197 21.60 1 69 1 0
#> 63.1 22.77 1 31 1 0
#> 5 16.43 1 51 0 1
#> 90 20.94 1 50 0 1
#> 107 11.18 1 54 1 0
#> 29.1 15.45 1 68 1 0
#> 89 11.44 1 NA 0 0
#> 100.1 16.07 1 60 0 0
#> 93 10.33 1 52 0 1
#> 197.1 21.60 1 69 1 0
#> 42 12.43 1 49 0 1
#> 108.1 18.29 1 39 0 1
#> 107.1 11.18 1 54 1 0
#> 40 18.00 1 28 1 0
#> 100.2 16.07 1 60 0 0
#> 125 15.65 1 67 1 0
#> 15 22.68 1 48 0 0
#> 30 17.43 1 78 0 0
#> 154 12.63 1 20 1 0
#> 127 3.53 1 62 0 1
#> 88 18.37 1 47 0 0
#> 114.1 13.68 1 NA 0 0
#> 63.2 22.77 1 31 1 0
#> 177 12.53 1 75 0 0
#> 57.1 14.46 1 45 0 1
#> 170 19.54 1 43 0 1
#> 60 13.15 1 38 1 0
#> 170.1 19.54 1 43 0 1
#> 139 21.49 1 63 1 0
#> 139.1 21.49 1 63 1 0
#> 89.1 11.44 1 NA 0 0
#> 57.2 14.46 1 45 0 1
#> 127.1 3.53 1 62 0 1
#> 179 18.63 1 42 0 0
#> 43 12.10 1 61 0 1
#> 153.2 21.33 1 55 1 0
#> 68 20.62 1 44 0 0
#> 140 12.68 1 59 1 0
#> 184 17.77 1 38 0 0
#> 125.1 15.65 1 67 1 0
#> 61 10.12 1 36 0 1
#> 181.1 16.46 1 45 0 1
#> 4 17.64 1 NA 0 1
#> 8 18.43 1 32 0 0
#> 97.1 19.14 1 65 0 1
#> 159.1 10.55 1 50 0 1
#> 13 14.34 1 54 0 1
#> 29.2 15.45 1 68 1 0
#> 41 18.02 1 40 1 0
#> 181.2 16.46 1 45 0 1
#> 100.3 16.07 1 60 0 0
#> 90.1 20.94 1 50 0 1
#> 155.2 13.08 1 26 0 0
#> 78.2 23.88 1 43 0 0
#> 25 6.32 1 34 1 0
#> 89.2 11.44 1 NA 0 0
#> 89.3 11.44 1 NA 0 0
#> 192 16.44 1 31 1 0
#> 150 20.33 1 48 0 0
#> 194.1 22.40 1 38 0 1
#> 15.1 22.68 1 48 0 0
#> 29.3 15.45 1 68 1 0
#> 29.4 15.45 1 68 1 0
#> 175 21.91 1 43 0 0
#> 14.1 12.89 1 21 0 0
#> 91 5.33 1 61 0 1
#> 149.1 8.37 1 33 1 0
#> 183.1 9.24 1 67 1 0
#> 69 23.23 1 25 0 1
#> 39 15.59 1 37 0 1
#> 88.1 18.37 1 47 0 0
#> 101 9.97 1 10 0 1
#> 38 24.00 0 31 1 0
#> 126 24.00 0 48 0 0
#> 200 24.00 0 64 0 0
#> 122 24.00 0 66 0 0
#> 53 24.00 0 32 0 1
#> 74 24.00 0 43 0 1
#> 28 24.00 0 67 1 0
#> 65 24.00 0 57 1 0
#> 118 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 17 24.00 0 38 0 1
#> 12 24.00 0 63 0 0
#> 132 24.00 0 55 0 0
#> 12.1 24.00 0 63 0 0
#> 112 24.00 0 61 0 0
#> 80 24.00 0 41 0 0
#> 67 24.00 0 25 0 0
#> 34 24.00 0 36 0 0
#> 165 24.00 0 47 0 0
#> 131 24.00 0 66 0 0
#> 151 24.00 0 42 0 0
#> 20 24.00 0 46 1 0
#> 75 24.00 0 21 1 0
#> 83 24.00 0 6 0 0
#> 182 24.00 0 35 0 0
#> 182.1 24.00 0 35 0 0
#> 143 24.00 0 51 0 0
#> 95.1 24.00 0 68 0 1
#> 186 24.00 0 45 1 0
#> 200.1 24.00 0 64 0 0
#> 34.1 24.00 0 36 0 0
#> 103 24.00 0 56 1 0
#> 116 24.00 0 58 0 1
#> 102 24.00 0 49 0 0
#> 38.1 24.00 0 31 1 0
#> 148 24.00 0 61 1 0
#> 151.1 24.00 0 42 0 0
#> 186.1 24.00 0 45 1 0
#> 71 24.00 0 51 0 0
#> 193 24.00 0 45 0 1
#> 185 24.00 0 44 1 0
#> 132.1 24.00 0 55 0 0
#> 186.2 24.00 0 45 1 0
#> 116.1 24.00 0 58 0 1
#> 27 24.00 0 63 1 0
#> 148.1 24.00 0 61 1 0
#> 112.1 24.00 0 61 0 0
#> 84 24.00 0 39 0 1
#> 121 24.00 0 57 1 0
#> 94 24.00 0 51 0 1
#> 20.1 24.00 0 46 1 0
#> 109 24.00 0 48 0 0
#> 17.1 24.00 0 38 0 1
#> 156 24.00 0 50 1 0
#> 115 24.00 0 NA 1 0
#> 74.1 24.00 0 43 0 1
#> 186.3 24.00 0 45 1 0
#> 137 24.00 0 45 1 0
#> 47 24.00 0 38 0 1
#> 33 24.00 0 53 0 0
#> 87 24.00 0 27 0 0
#> 191 24.00 0 60 0 1
#> 21 24.00 0 47 0 0
#> 178 24.00 0 52 1 0
#> 122.1 24.00 0 66 0 0
#> 22 24.00 0 52 1 0
#> 172 24.00 0 41 0 0
#> 135 24.00 0 58 1 0
#> 138 24.00 0 44 1 0
#> 122.2 24.00 0 66 0 0
#> 144 24.00 0 28 0 1
#> 148.2 24.00 0 61 1 0
#> 31 24.00 0 36 0 1
#> 75.1 24.00 0 21 1 0
#> 173 24.00 0 19 0 1
#> 74.2 24.00 0 43 0 1
#> 74.3 24.00 0 43 0 1
#> 71.1 24.00 0 51 0 0
#> 142 24.00 0 53 0 0
#> 120 24.00 0 68 0 1
#> 198 24.00 0 66 0 1
#> 156.1 24.00 0 50 1 0
#> 34.2 24.00 0 36 0 0
#> 137.1 24.00 0 45 1 0
#> 67.1 24.00 0 25 0 0
#> 103.1 24.00 0 56 1 0
#> 11 24.00 0 42 0 1
#> 174 24.00 0 49 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.315 NA NA NA
#> 2 age, Cure model 0.00275 NA NA NA
#> 3 grade_ii, Cure model 0.361 NA NA NA
#> 4 grade_iii, Cure model 0.703 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00887 NA NA NA
#> 2 grade_ii, Survival model 0.256 NA NA NA
#> 3 grade_iii, Survival model 0.470 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.315478 0.002749 0.361081 0.703484
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 257 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.315478330 0.002748941 0.361081153 0.703483987
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.008872266 0.255888626 0.470015041
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.49118443 0.75034540 0.95595530 0.22646670 0.49118443 0.82945902
#> [7] 0.76345189 0.84109297 0.71044983 0.57300795 0.67526232 0.93538904
#> [13] 0.80599524 0.09020731 0.17856306 0.46019268 0.62177822 0.09020731
#> [19] 0.66781076 0.91955123 0.94577165 0.53739795 0.85828334 0.79989389
#> [25] 0.84109297 0.24826154 0.49118443 0.42740532 0.97582223 0.33267561
#> [31] 0.79376176 0.42740532 0.96592610 0.95595530 0.49118443 0.90884238
#> [37] 0.37697410 0.24826154 0.70348407 0.47106371 0.89794171 0.76345189
#> [43] 0.71044983 0.92487354 0.37697410 0.88680050 0.62177822 0.89794171
#> [49] 0.64499568 0.71044983 0.73717987 0.29951426 0.66027555 0.87545890
#> [55] 0.99048318 0.60577554 0.24826154 0.88114695 0.80599524 0.55569622
#> [61] 0.83529239 0.55569622 0.40318020 0.40318020 0.80599524 0.99048318
#> [67] 0.58940422 0.89240151 0.42740532 0.52801849 0.86975073 0.65265354
#> [73] 0.73717987 0.93014915 0.67526232 0.59760828 0.57300795 0.90884238
#> [79] 0.82361117 0.76345189 0.63727773 0.67526232 0.71044983 0.47106371
#> [85] 0.84109297 0.09020731 0.98073547 0.69641218 0.54658774 0.33267561
#> [91] 0.29951426 0.76345189 0.76345189 0.36218933 0.85828334 0.98563040
#> [97] 0.96592610 0.94577165 0.20390987 0.75693330 0.60577554 0.94059107
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 190 6 16 113 190.1 81 29 155 100 97 181 145 57
#> 20.81 15.64 8.71 22.86 20.81 14.06 15.45 13.08 16.07 19.14 16.46 10.07 14.46
#> 78 164 99 108 78.1 106 52 183 128 14 133 155.1 63
#> 23.88 23.60 21.19 18.29 23.88 16.67 10.42 9.24 20.35 12.89 14.65 13.08 22.77
#> 190.2 153 77 194 157 153.1 149 16.1 190.3 159 197 63.1 5
#> 20.81 21.33 7.27 22.40 15.10 21.33 8.37 8.71 20.81 10.55 21.60 22.77 16.43
#> 90 107 29.1 100.1 93 197.1 42 108.1 107.1 40 100.2 125 15
#> 20.94 11.18 15.45 16.07 10.33 21.60 12.43 18.29 11.18 18.00 16.07 15.65 22.68
#> 30 154 127 88 63.2 177 57.1 170 60 170.1 139 139.1 57.2
#> 17.43 12.63 3.53 18.37 22.77 12.53 14.46 19.54 13.15 19.54 21.49 21.49 14.46
#> 127.1 179 43 153.2 68 140 184 125.1 61 181.1 8 97.1 159.1
#> 3.53 18.63 12.10 21.33 20.62 12.68 17.77 15.65 10.12 16.46 18.43 19.14 10.55
#> 13 29.2 41 181.2 100.3 90.1 155.2 78.2 25 192 150 194.1 15.1
#> 14.34 15.45 18.02 16.46 16.07 20.94 13.08 23.88 6.32 16.44 20.33 22.40 22.68
#> 29.3 29.4 175 14.1 91 149.1 183.1 69 39 88.1 101 38 126
#> 15.45 15.45 21.91 12.89 5.33 8.37 9.24 23.23 15.59 18.37 9.97 24.00 24.00
#> 200 122 53 74 28 65 118 95 17 12 132 12.1 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 67 34 165 131 151 20 75 83 182 182.1 143 95.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 200.1 34.1 103 116 102 38.1 148 151.1 186.1 71 193 185
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.1 186.2 116.1 27 148.1 112.1 84 121 94 20.1 109 17.1 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74.1 186.3 137 47 33 87 191 21 178 122.1 22 172 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 122.2 144 148.2 31 75.1 173 74.2 74.3 71.1 142 120 198
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156.1 34.2 137.1 67.1 103.1 11 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[60]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002205932 0.699173397 0.405745407
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.93908468 0.01798021 0.22605330
#> grade_iii, Cure model
#> 0.90918786
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 14 12.89 1 21 0 0
#> 192 16.44 1 31 1 0
#> 192.1 16.44 1 31 1 0
#> 180 14.82 1 37 0 0
#> 6 15.64 1 39 0 0
#> 188 16.16 1 46 0 1
#> 117 17.46 1 26 0 1
#> 92 22.92 1 47 0 1
#> 192.2 16.44 1 31 1 0
#> 180.1 14.82 1 37 0 0
#> 77 7.27 1 67 0 1
#> 24 23.89 1 38 0 0
#> 181 16.46 1 45 0 1
#> 66 22.13 1 53 0 0
#> 199 19.81 1 NA 0 1
#> 92.1 22.92 1 47 0 1
#> 88 18.37 1 47 0 0
#> 16 8.71 1 71 0 1
#> 23 16.92 1 61 0 0
#> 24.1 23.89 1 38 0 0
#> 57 14.46 1 45 0 1
#> 86 23.81 1 58 0 1
#> 39 15.59 1 37 0 1
#> 157 15.10 1 47 0 0
#> 190 20.81 1 42 1 0
#> 16.1 8.71 1 71 0 1
#> 61 10.12 1 36 0 1
#> 36 21.19 1 48 0 1
#> 111 17.45 1 47 0 1
#> 188.1 16.16 1 46 0 1
#> 134 17.81 1 47 1 0
#> 79 16.23 1 54 1 0
#> 179 18.63 1 42 0 0
#> 78 23.88 1 43 0 0
#> 106 16.67 1 49 1 0
#> 25 6.32 1 34 1 0
#> 40 18.00 1 28 1 0
#> 197 21.60 1 69 1 0
#> 69 23.23 1 25 0 1
#> 90 20.94 1 50 0 1
#> 157.1 15.10 1 47 0 0
#> 30 17.43 1 78 0 0
#> 187 9.92 1 39 1 0
#> 106.1 16.67 1 49 1 0
#> 177 12.53 1 75 0 0
#> 88.1 18.37 1 47 0 0
#> 69.1 23.23 1 25 0 1
#> 68 20.62 1 44 0 0
#> 197.1 21.60 1 69 1 0
#> 14.1 12.89 1 21 0 0
#> 61.1 10.12 1 36 0 1
#> 124 9.73 1 NA 1 0
#> 133 14.65 1 57 0 0
#> 97 19.14 1 65 0 1
#> 52 10.42 1 52 0 1
#> 129 23.41 1 53 1 0
#> 139 21.49 1 63 1 0
#> 36.1 21.19 1 48 0 1
#> 66.1 22.13 1 53 0 0
#> 106.2 16.67 1 49 1 0
#> 4 17.64 1 NA 0 1
#> 78.1 23.88 1 43 0 0
#> 136 21.83 1 43 0 1
#> 41 18.02 1 40 1 0
#> 169 22.41 1 46 0 0
#> 190.1 20.81 1 42 1 0
#> 57.1 14.46 1 45 0 1
#> 29 15.45 1 68 1 0
#> 15 22.68 1 48 0 0
#> 8 18.43 1 32 0 0
#> 89 11.44 1 NA 0 0
#> 68.1 20.62 1 44 0 0
#> 180.2 14.82 1 37 0 0
#> 107 11.18 1 54 1 0
#> 79.1 16.23 1 54 1 0
#> 194 22.40 1 38 0 1
#> 66.2 22.13 1 53 0 0
#> 37 12.52 1 57 1 0
#> 6.1 15.64 1 39 0 0
#> 184 17.77 1 38 0 0
#> 199.1 19.81 1 NA 0 1
#> 81 14.06 1 34 0 0
#> 92.2 22.92 1 47 0 1
#> 29.1 15.45 1 68 1 0
#> 134.1 17.81 1 47 1 0
#> 15.1 22.68 1 48 0 0
#> 168 23.72 1 70 0 0
#> 123 13.00 1 44 1 0
#> 58 19.34 1 39 0 0
#> 181.1 16.46 1 45 0 1
#> 55 19.34 1 69 0 1
#> 110 17.56 1 65 0 1
#> 124.1 9.73 1 NA 1 0
#> 36.2 21.19 1 48 0 1
#> 190.2 20.81 1 42 1 0
#> 168.1 23.72 1 70 0 0
#> 37.1 12.52 1 57 1 0
#> 111.1 17.45 1 47 0 1
#> 197.2 21.60 1 69 1 0
#> 68.2 20.62 1 44 0 0
#> 175 21.91 1 43 0 0
#> 81.1 14.06 1 34 0 0
#> 13 14.34 1 54 0 1
#> 184.1 17.77 1 38 0 0
#> 16.2 8.71 1 71 0 1
#> 125 15.65 1 67 1 0
#> 168.2 23.72 1 70 0 0
#> 107.1 11.18 1 54 1 0
#> 93 10.33 1 52 0 1
#> 8.1 18.43 1 32 0 0
#> 170 19.54 1 43 0 1
#> 45 17.42 1 54 0 1
#> 62 24.00 0 71 0 0
#> 75 24.00 0 21 1 0
#> 185 24.00 0 44 1 0
#> 102 24.00 0 49 0 0
#> 80 24.00 0 41 0 0
#> 131 24.00 0 66 0 0
#> 120 24.00 0 68 0 1
#> 132 24.00 0 55 0 0
#> 200 24.00 0 64 0 0
#> 67 24.00 0 25 0 0
#> 7 24.00 0 37 1 0
#> 17 24.00 0 38 0 1
#> 196 24.00 0 19 0 0
#> 98 24.00 0 34 1 0
#> 87 24.00 0 27 0 0
#> 64 24.00 0 43 0 0
#> 151 24.00 0 42 0 0
#> 62.1 24.00 0 71 0 0
#> 141 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 33 24.00 0 53 0 0
#> 33.1 24.00 0 53 0 0
#> 34 24.00 0 36 0 0
#> 172 24.00 0 41 0 0
#> 120.1 24.00 0 68 0 1
#> 33.2 24.00 0 53 0 0
#> 75.1 24.00 0 21 1 0
#> 9 24.00 0 31 1 0
#> 44 24.00 0 56 0 0
#> 33.3 24.00 0 53 0 0
#> 144 24.00 0 28 0 1
#> 109 24.00 0 48 0 0
#> 53 24.00 0 32 0 1
#> 151.1 24.00 0 42 0 0
#> 143 24.00 0 51 0 0
#> 152 24.00 0 36 0 1
#> 152.1 24.00 0 36 0 1
#> 98.1 24.00 0 34 1 0
#> 116 24.00 0 58 0 1
#> 21 24.00 0 47 0 0
#> 47 24.00 0 38 0 1
#> 193 24.00 0 45 0 1
#> 137 24.00 0 45 1 0
#> 21.1 24.00 0 47 0 0
#> 132.1 24.00 0 55 0 0
#> 118 24.00 0 44 1 0
#> 67.1 24.00 0 25 0 0
#> 138 24.00 0 44 1 0
#> 71 24.00 0 51 0 0
#> 73 24.00 0 NA 0 1
#> 7.1 24.00 0 37 1 0
#> 53.1 24.00 0 32 0 1
#> 196.1 24.00 0 19 0 0
#> 98.2 24.00 0 34 1 0
#> 141.1 24.00 0 44 1 0
#> 98.3 24.00 0 34 1 0
#> 182 24.00 0 35 0 0
#> 103 24.00 0 56 1 0
#> 46 24.00 0 71 0 0
#> 74 24.00 0 43 0 1
#> 143.1 24.00 0 51 0 0
#> 156 24.00 0 50 1 0
#> 172.1 24.00 0 41 0 0
#> 116.1 24.00 0 58 0 1
#> 186 24.00 0 45 1 0
#> 98.4 24.00 0 34 1 0
#> 118.1 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 48 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 12 24.00 0 63 0 0
#> 2 24.00 0 9 0 0
#> 182.1 24.00 0 35 0 0
#> 46.1 24.00 0 71 0 0
#> 12.1 24.00 0 63 0 0
#> 109.1 24.00 0 48 0 0
#> 141.2 24.00 0 44 1 0
#> 122 24.00 0 66 0 0
#> 121 24.00 0 57 1 0
#> 103.1 24.00 0 56 1 0
#> 162 24.00 0 51 0 0
#> 53.2 24.00 0 32 0 1
#> 17.1 24.00 0 38 0 1
#> 148 24.00 0 61 1 0
#> 94 24.00 0 51 0 1
#> 132.2 24.00 0 55 0 0
#> 1 24.00 0 23 1 0
#> 35 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.939 NA NA NA
#> 2 age, Cure model 0.0180 NA NA NA
#> 3 grade_ii, Cure model 0.226 NA NA NA
#> 4 grade_iii, Cure model 0.909 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00221 NA NA NA
#> 2 grade_ii, Survival model 0.699 NA NA NA
#> 3 grade_iii, Survival model 0.406 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.93908 0.01798 0.22605 0.90919
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.7
#> Residual Deviance: 256.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.93908468 0.01798021 0.22605330 0.90918786
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002205932 0.699173397 0.405745407
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.87482332 0.68115084 0.68115084 0.79841063 0.74441657 0.72092600
#> [7] 0.58733523 0.16482908 0.68115084 0.79841063 0.98559412 0.01347989
#> [13] 0.66455237 0.24532267 0.16482908 0.50612226 0.96402971 0.63087913
#> [19] 0.01347989 0.82905762 0.06908626 0.75999587 0.78308812 0.38508551
#> [25] 0.96402971 0.94212475 0.34519042 0.59614314 0.72092600 0.54317382
#> [31] 0.70513060 0.47817980 0.03999034 0.63958862 0.99281971 0.53404470
#> [37] 0.30323388 0.13986714 0.37497628 0.78308812 0.61344987 0.95674084
#> [43] 0.63958862 0.88997170 0.50612226 0.13986714 0.41284956 0.30323388
#> [49] 0.87482332 0.94212475 0.82133528 0.46883804 0.92734307 0.12566478
#> [55] 0.33463417 0.34519042 0.24532267 0.63958862 0.03999034 0.29146502
#> [61] 0.52477430 0.22153061 0.38508551 0.82905762 0.76779510 0.19827837
#> [67] 0.48753775 0.41284956 0.79841063 0.91256103 0.70513060 0.23354160
#> [73] 0.24532267 0.89758833 0.74441657 0.56080052 0.85197621 0.16482908
#> [79] 0.76779510 0.54317382 0.19827837 0.08445535 0.86722204 0.45023056
#> [85] 0.66455237 0.45023056 0.57847192 0.34519042 0.38508551 0.08445535
#> [91] 0.89758833 0.59614314 0.30323388 0.41284956 0.27952039 0.85197621
#> [97] 0.84432883 0.56080052 0.96402971 0.73659930 0.08445535 0.91256103
#> [103] 0.93474378 0.48753775 0.44078806 0.62218475 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000
#>
#> $Time
#> 14 192 192.1 180 6 188 117 92 192.2 180.1 77 24 181
#> 12.89 16.44 16.44 14.82 15.64 16.16 17.46 22.92 16.44 14.82 7.27 23.89 16.46
#> 66 92.1 88 16 23 24.1 57 86 39 157 190 16.1 61
#> 22.13 22.92 18.37 8.71 16.92 23.89 14.46 23.81 15.59 15.10 20.81 8.71 10.12
#> 36 111 188.1 134 79 179 78 106 25 40 197 69 90
#> 21.19 17.45 16.16 17.81 16.23 18.63 23.88 16.67 6.32 18.00 21.60 23.23 20.94
#> 157.1 30 187 106.1 177 88.1 69.1 68 197.1 14.1 61.1 133 97
#> 15.10 17.43 9.92 16.67 12.53 18.37 23.23 20.62 21.60 12.89 10.12 14.65 19.14
#> 52 129 139 36.1 66.1 106.2 78.1 136 41 169 190.1 57.1 29
#> 10.42 23.41 21.49 21.19 22.13 16.67 23.88 21.83 18.02 22.41 20.81 14.46 15.45
#> 15 8 68.1 180.2 107 79.1 194 66.2 37 6.1 184 81 92.2
#> 22.68 18.43 20.62 14.82 11.18 16.23 22.40 22.13 12.52 15.64 17.77 14.06 22.92
#> 29.1 134.1 15.1 168 123 58 181.1 55 110 36.2 190.2 168.1 37.1
#> 15.45 17.81 22.68 23.72 13.00 19.34 16.46 19.34 17.56 21.19 20.81 23.72 12.52
#> 111.1 197.2 68.2 175 81.1 13 184.1 16.2 125 168.2 107.1 93 8.1
#> 17.45 21.60 20.62 21.91 14.06 14.34 17.77 8.71 15.65 23.72 11.18 10.33 18.43
#> 170 45 62 75 185 102 80 131 120 132 200 67 7
#> 19.54 17.42 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17 196 98 87 64 151 62.1 141 82 33 33.1 34 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120.1 33.2 75.1 9 44 33.3 144 109 53 151.1 143 152 152.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.1 116 21 47 193 137 21.1 132.1 118 67.1 138 71 7.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53.1 196.1 98.2 141.1 98.3 182 103 46 74 143.1 156 172.1 116.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 98.4 118.1 112 48 174 12 2 182.1 46.1 12.1 109.1 141.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 121 103.1 162 53.2 17.1 148 94 132.2 1 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[61]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.006044965 0.895329808 0.573788956
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.87485553 0.01709282 0.06286355
#> grade_iii, Cure model
#> 0.62521258
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 77 7.27 1 67 0 1
#> 6 15.64 1 39 0 0
#> 101 9.97 1 10 0 1
#> 123 13.00 1 44 1 0
#> 76 19.22 1 54 0 1
#> 5 16.43 1 51 0 1
#> 171 16.57 1 41 0 1
#> 125 15.65 1 67 1 0
#> 154 12.63 1 20 1 0
#> 111 17.45 1 47 0 1
#> 81 14.06 1 34 0 0
#> 134 17.81 1 47 1 0
#> 113 22.86 1 34 0 0
#> 114 13.68 1 NA 0 0
#> 79 16.23 1 54 1 0
#> 124 9.73 1 NA 1 0
#> 117 17.46 1 26 0 1
#> 15 22.68 1 48 0 0
#> 78 23.88 1 43 0 0
#> 36 21.19 1 48 0 1
#> 100 16.07 1 60 0 0
#> 86 23.81 1 58 0 1
#> 100.1 16.07 1 60 0 0
#> 114.1 13.68 1 NA 0 0
#> 184 17.77 1 38 0 0
#> 166 19.98 1 48 0 0
#> 99 21.19 1 38 0 1
#> 76.1 19.22 1 54 0 1
#> 59 10.16 1 NA 1 0
#> 29 15.45 1 68 1 0
#> 106 16.67 1 49 1 0
#> 107 11.18 1 54 1 0
#> 14 12.89 1 21 0 0
#> 139 21.49 1 63 1 0
#> 177 12.53 1 75 0 0
#> 51 18.23 1 83 0 1
#> 179 18.63 1 42 0 0
#> 158 20.14 1 74 1 0
#> 56 12.21 1 60 0 0
#> 159 10.55 1 50 0 1
#> 14.1 12.89 1 21 0 0
#> 124.1 9.73 1 NA 1 0
#> 23 16.92 1 61 0 0
#> 24 23.89 1 38 0 0
#> 92 22.92 1 47 0 1
#> 76.2 19.22 1 54 0 1
#> 76.3 19.22 1 54 0 1
#> 145 10.07 1 65 1 0
#> 13 14.34 1 54 0 1
#> 93 10.33 1 52 0 1
#> 66 22.13 1 53 0 0
#> 195 11.76 1 NA 1 0
#> 187 9.92 1 39 1 0
#> 194 22.40 1 38 0 1
#> 51.1 18.23 1 83 0 1
#> 70 7.38 1 30 1 0
#> 32 20.90 1 37 1 0
#> 129 23.41 1 53 1 0
#> 6.1 15.64 1 39 0 0
#> 168 23.72 1 70 0 0
#> 180 14.82 1 37 0 0
#> 150 20.33 1 48 0 0
#> 45 17.42 1 54 0 1
#> 171.1 16.57 1 41 0 1
#> 32.1 20.90 1 37 1 0
#> 55 19.34 1 69 0 1
#> 43 12.10 1 61 0 1
#> 90 20.94 1 50 0 1
#> 179.1 18.63 1 42 0 0
#> 158.1 20.14 1 74 1 0
#> 16 8.71 1 71 0 1
#> 159.1 10.55 1 50 0 1
#> 113.1 22.86 1 34 0 0
#> 150.1 20.33 1 48 0 0
#> 125.1 15.65 1 67 1 0
#> 175 21.91 1 43 0 0
#> 89 11.44 1 NA 0 0
#> 155 13.08 1 26 0 0
#> 51.2 18.23 1 83 0 1
#> 114.2 13.68 1 NA 0 0
#> 100.2 16.07 1 60 0 0
#> 58 19.34 1 39 0 0
#> 110 17.56 1 65 0 1
#> 189 10.51 1 NA 1 0
#> 175.1 21.91 1 43 0 0
#> 136 21.83 1 43 0 1
#> 110.1 17.56 1 65 0 1
#> 78.1 23.88 1 43 0 0
#> 100.3 16.07 1 60 0 0
#> 199 19.81 1 NA 0 1
#> 96 14.54 1 33 0 1
#> 36.1 21.19 1 48 0 1
#> 24.1 23.89 1 38 0 0
#> 37 12.52 1 57 1 0
#> 37.1 12.52 1 57 1 0
#> 108 18.29 1 39 0 1
#> 29.1 15.45 1 68 1 0
#> 113.2 22.86 1 34 0 0
#> 139.1 21.49 1 63 1 0
#> 70.1 7.38 1 30 1 0
#> 114.3 13.68 1 NA 0 0
#> 167 15.55 1 56 1 0
#> 114.4 13.68 1 NA 0 0
#> 184.1 17.77 1 38 0 0
#> 76.4 19.22 1 54 0 1
#> 159.2 10.55 1 50 0 1
#> 13.1 14.34 1 54 0 1
#> 164 23.60 1 76 0 1
#> 139.2 21.49 1 63 1 0
#> 125.2 15.65 1 67 1 0
#> 140 12.68 1 59 1 0
#> 15.1 22.68 1 48 0 0
#> 132 24.00 0 55 0 0
#> 9 24.00 0 31 1 0
#> 200 24.00 0 64 0 0
#> 95 24.00 0 68 0 1
#> 65 24.00 0 57 1 0
#> 62 24.00 0 71 0 0
#> 31 24.00 0 36 0 1
#> 2 24.00 0 9 0 0
#> 38 24.00 0 31 1 0
#> 84 24.00 0 39 0 1
#> 17 24.00 0 38 0 1
#> 193 24.00 0 45 0 1
#> 173 24.00 0 19 0 1
#> 161 24.00 0 45 0 0
#> 73 24.00 0 NA 0 1
#> 185 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 28 24.00 0 67 1 0
#> 200.1 24.00 0 64 0 0
#> 196 24.00 0 19 0 0
#> 27 24.00 0 63 1 0
#> 109 24.00 0 48 0 0
#> 144 24.00 0 28 0 1
#> 11 24.00 0 42 0 1
#> 80 24.00 0 41 0 0
#> 73.1 24.00 0 NA 0 1
#> 160 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 122 24.00 0 66 0 0
#> 161.1 24.00 0 45 0 0
#> 75 24.00 0 21 1 0
#> 191 24.00 0 60 0 1
#> 95.1 24.00 0 68 0 1
#> 104 24.00 0 50 1 0
#> 2.1 24.00 0 9 0 0
#> 147 24.00 0 76 1 0
#> 121 24.00 0 57 1 0
#> 64 24.00 0 43 0 0
#> 87 24.00 0 27 0 0
#> 143 24.00 0 51 0 0
#> 138 24.00 0 44 1 0
#> 102 24.00 0 49 0 0
#> 126 24.00 0 48 0 0
#> 126.1 24.00 0 48 0 0
#> 34 24.00 0 36 0 0
#> 122.1 24.00 0 66 0 0
#> 94 24.00 0 51 0 1
#> 71.1 24.00 0 51 0 0
#> 74 24.00 0 43 0 1
#> 74.1 24.00 0 43 0 1
#> 147.1 24.00 0 76 1 0
#> 165 24.00 0 47 0 0
#> 22 24.00 0 52 1 0
#> 74.2 24.00 0 43 0 1
#> 95.2 24.00 0 68 0 1
#> 185.1 24.00 0 44 1 0
#> 178 24.00 0 52 1 0
#> 67 24.00 0 25 0 0
#> 196.1 24.00 0 19 0 0
#> 176 24.00 0 43 0 1
#> 28.1 24.00 0 67 1 0
#> 185.2 24.00 0 44 1 0
#> 198 24.00 0 66 0 1
#> 122.2 24.00 0 66 0 0
#> 27.1 24.00 0 63 1 0
#> 160.1 24.00 0 31 1 0
#> 165.1 24.00 0 47 0 0
#> 112 24.00 0 61 0 0
#> 126.2 24.00 0 48 0 0
#> 44 24.00 0 56 0 0
#> 98 24.00 0 34 1 0
#> 147.2 24.00 0 76 1 0
#> 31.1 24.00 0 36 0 1
#> 161.2 24.00 0 45 0 0
#> 73.2 24.00 0 NA 0 1
#> 144.1 24.00 0 28 0 1
#> 131 24.00 0 66 0 0
#> 135 24.00 0 58 1 0
#> 186 24.00 0 45 1 0
#> 46 24.00 0 71 0 0
#> 48 24.00 0 31 1 0
#> 83 24.00 0 6 0 0
#> 173.1 24.00 0 19 0 1
#> 119 24.00 0 17 0 0
#> 109.1 24.00 0 48 0 0
#> 80.1 24.00 0 41 0 0
#> 80.2 24.00 0 41 0 0
#> 193.1 24.00 0 45 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.875 NA NA NA
#> 2 age, Cure model 0.0171 NA NA NA
#> 3 grade_ii, Cure model 0.0629 NA NA NA
#> 4 grade_iii, Cure model 0.625 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00604 NA NA NA
#> 2 grade_ii, Survival model 0.895 NA NA NA
#> 3 grade_iii, Survival model 0.574 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.87486 0.01709 0.06286 0.62521
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 255.2
#> Residual Deviance: 248.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.87485553 0.01709282 0.06286355 0.62521258
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.006044965 0.895329808 0.573788956
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.99195274 0.71684246 0.95120891 0.81475244 0.41493695 0.63502269
#> [7] 0.61654520 0.68995800 0.84973511 0.57855679 0.79706176 0.52079227
#> [13] 0.12030005 0.64428835 0.56896720 0.15541537 0.02789166 0.27954006
#> [19] 0.65345301 0.05282323 0.65345301 0.53046721 0.38438758 0.27954006
#> [25] 0.41493695 0.74401463 0.60712660 0.90106924 0.82352134 0.24573559
#> [31] 0.85835675 0.49185889 0.46224812 0.36426517 0.88398273 0.90954170
#> [37] 0.82352134 0.59758657 0.00792557 0.10799937 0.41493695 0.41493695
#> [43] 0.94288232 0.77951914 0.93450746 0.19362040 0.95948688 0.18082015
#> [49] 0.49185889 0.97589967 0.32303618 0.09521152 0.71684246 0.06636493
#> [55] 0.76171728 0.34349476 0.58809328 0.61654520 0.32303618 0.39465262
#> [61] 0.89253529 0.31195707 0.46224812 0.36426517 0.96769869 0.90954170
#> [67] 0.12030005 0.34349476 0.68995800 0.20665715 0.80590004 0.49185889
#> [73] 0.65345301 0.39465262 0.54978398 0.20665715 0.23263802 0.54978398
#> [79] 0.02789166 0.65345301 0.77064155 0.27954006 0.00792557 0.86701007
#> [85] 0.86701007 0.48197473 0.74401463 0.12030005 0.24573559 0.97589967
#> [91] 0.73497523 0.53046721 0.41493695 0.90954170 0.77951914 0.08094006
#> [97] 0.24573559 0.68995800 0.84100996 0.15541537 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 77 6 101 123 76 5 171 125 154 111 81 134 113
#> 7.27 15.64 9.97 13.00 19.22 16.43 16.57 15.65 12.63 17.45 14.06 17.81 22.86
#> 79 117 15 78 36 100 86 100.1 184 166 99 76.1 29
#> 16.23 17.46 22.68 23.88 21.19 16.07 23.81 16.07 17.77 19.98 21.19 19.22 15.45
#> 106 107 14 139 177 51 179 158 56 159 14.1 23 24
#> 16.67 11.18 12.89 21.49 12.53 18.23 18.63 20.14 12.21 10.55 12.89 16.92 23.89
#> 92 76.2 76.3 145 13 93 66 187 194 51.1 70 32 129
#> 22.92 19.22 19.22 10.07 14.34 10.33 22.13 9.92 22.40 18.23 7.38 20.90 23.41
#> 6.1 168 180 150 45 171.1 32.1 55 43 90 179.1 158.1 16
#> 15.64 23.72 14.82 20.33 17.42 16.57 20.90 19.34 12.10 20.94 18.63 20.14 8.71
#> 159.1 113.1 150.1 125.1 175 155 51.2 100.2 58 110 175.1 136 110.1
#> 10.55 22.86 20.33 15.65 21.91 13.08 18.23 16.07 19.34 17.56 21.91 21.83 17.56
#> 78.1 100.3 96 36.1 24.1 37 37.1 108 29.1 113.2 139.1 70.1 167
#> 23.88 16.07 14.54 21.19 23.89 12.52 12.52 18.29 15.45 22.86 21.49 7.38 15.55
#> 184.1 76.4 159.2 13.1 164 139.2 125.2 140 15.1 132 9 200 95
#> 17.77 19.22 10.55 14.34 23.60 21.49 15.65 12.68 22.68 24.00 24.00 24.00 24.00
#> 65 62 31 2 38 84 17 193 173 161 185 82 28
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200.1 196 27 109 144 11 80 160 71 122 161.1 75 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95.1 104 2.1 147 121 64 87 143 138 102 126 126.1 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122.1 94 71.1 74 74.1 147.1 165 22 74.2 95.2 185.1 178 67
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196.1 176 28.1 185.2 198 122.2 27.1 160.1 165.1 112 126.2 44 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147.2 31.1 161.2 144.1 131 135 186 46 48 83 173.1 119 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80.1 80.2 193.1
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[62]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003358758 0.238431705 0.177637238
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.00626071 0.02235227 -0.43361146
#> grade_iii, Cure model
#> 0.74286743
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 106 16.67 1 49 1 0
#> 56 12.21 1 60 0 0
#> 130 16.47 1 53 0 1
#> 10 10.53 1 34 0 0
#> 106.1 16.67 1 49 1 0
#> 63 22.77 1 31 1 0
#> 41 18.02 1 40 1 0
#> 97 19.14 1 65 0 1
#> 86 23.81 1 58 0 1
#> 5 16.43 1 51 0 1
#> 179 18.63 1 42 0 0
#> 59 10.16 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 51 18.23 1 83 0 1
#> 5.1 16.43 1 51 0 1
#> 97.1 19.14 1 65 0 1
#> 6 15.64 1 39 0 0
#> 16 8.71 1 71 0 1
#> 39 15.59 1 37 0 1
#> 197 21.60 1 69 1 0
#> 51.1 18.23 1 83 0 1
#> 170 19.54 1 43 0 1
#> 85 16.44 1 36 0 0
#> 39.1 15.59 1 37 0 1
#> 100 16.07 1 60 0 0
#> 100.1 16.07 1 60 0 0
#> 155 13.08 1 26 0 0
#> 4 17.64 1 NA 0 1
#> 43 12.10 1 61 0 1
#> 86.1 23.81 1 58 0 1
#> 153 21.33 1 55 1 0
#> 170.1 19.54 1 43 0 1
#> 171 16.57 1 41 0 1
#> 89 11.44 1 NA 0 0
#> 88 18.37 1 47 0 0
#> 93 10.33 1 52 0 1
#> 99 21.19 1 38 0 1
#> 175 21.91 1 43 0 0
#> 23 16.92 1 61 0 0
#> 184 17.77 1 38 0 0
#> 188 16.16 1 46 0 1
#> 188.1 16.16 1 46 0 1
#> 199 19.81 1 NA 0 1
#> 41.1 18.02 1 40 1 0
#> 127 3.53 1 62 0 1
#> 70 7.38 1 30 1 0
#> 6.1 15.64 1 39 0 0
#> 190 20.81 1 42 1 0
#> 51.2 18.23 1 83 0 1
#> 89.1 11.44 1 NA 0 0
#> 63.1 22.77 1 31 1 0
#> 50 10.02 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 92 22.92 1 47 0 1
#> 197.1 21.60 1 69 1 0
#> 43.1 12.10 1 61 0 1
#> 96 14.54 1 33 0 1
#> 49 12.19 1 48 1 0
#> 61 10.12 1 36 0 1
#> 153.1 21.33 1 55 1 0
#> 59.1 10.16 1 NA 1 0
#> 43.2 12.10 1 61 0 1
#> 10.1 10.53 1 34 0 0
#> 8 18.43 1 32 0 0
#> 78 23.88 1 43 0 0
#> 113 22.86 1 34 0 0
#> 5.2 16.43 1 51 0 1
#> 177 12.53 1 75 0 0
#> 24 23.89 1 38 0 0
#> 76 19.22 1 54 0 1
#> 136 21.83 1 43 0 1
#> 150 20.33 1 48 0 0
#> 77 7.27 1 67 0 1
#> 117 17.46 1 26 0 1
#> 77.1 7.27 1 67 0 1
#> 164 23.60 1 76 0 1
#> 101 9.97 1 10 0 1
#> 49.1 12.19 1 48 1 0
#> 189 10.51 1 NA 1 0
#> 55 19.34 1 69 0 1
#> 5.3 16.43 1 51 0 1
#> 26 15.77 1 49 0 1
#> 56.1 12.21 1 60 0 0
#> 158 20.14 1 74 1 0
#> 37 12.52 1 57 1 0
#> 6.2 15.64 1 39 0 0
#> 89.2 11.44 1 NA 0 0
#> 100.2 16.07 1 60 0 0
#> 76.1 19.22 1 54 0 1
#> 86.2 23.81 1 58 0 1
#> 58 19.34 1 39 0 0
#> 167.1 15.55 1 56 1 0
#> 189.1 10.51 1 NA 1 0
#> 128 20.35 1 35 0 1
#> 43.3 12.10 1 61 0 1
#> 99.1 21.19 1 38 0 1
#> 88.1 18.37 1 47 0 0
#> 155.1 13.08 1 26 0 0
#> 57 14.46 1 45 0 1
#> 55.1 19.34 1 69 0 1
#> 123 13.00 1 44 1 0
#> 180 14.82 1 37 0 0
#> 57.1 14.46 1 45 0 1
#> 37.1 12.52 1 57 1 0
#> 42 12.43 1 49 0 1
#> 107 11.18 1 54 1 0
#> 106.2 16.67 1 49 1 0
#> 192 16.44 1 31 1 0
#> 42.1 12.43 1 49 0 1
#> 79 16.23 1 54 1 0
#> 107.1 11.18 1 54 1 0
#> 183 9.24 1 67 1 0
#> 80 24.00 0 41 0 0
#> 74 24.00 0 43 0 1
#> 151 24.00 0 42 0 0
#> 165 24.00 0 47 0 0
#> 143 24.00 0 51 0 0
#> 121 24.00 0 57 1 0
#> 186 24.00 0 45 1 0
#> 72 24.00 0 40 0 1
#> 116 24.00 0 58 0 1
#> 65 24.00 0 57 1 0
#> 9 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 98 24.00 0 34 1 0
#> 62 24.00 0 71 0 0
#> 7 24.00 0 37 1 0
#> 65.1 24.00 0 57 1 0
#> 174 24.00 0 49 1 0
#> 1 24.00 0 23 1 0
#> 22 24.00 0 52 1 0
#> 87 24.00 0 27 0 0
#> 11 24.00 0 42 0 1
#> 160 24.00 0 31 1 0
#> 102 24.00 0 49 0 0
#> 147 24.00 0 76 1 0
#> 74.1 24.00 0 43 0 1
#> 146 24.00 0 63 1 0
#> 38 24.00 0 31 1 0
#> 54 24.00 0 53 1 0
#> 137 24.00 0 45 1 0
#> 161 24.00 0 45 0 0
#> 132 24.00 0 55 0 0
#> 21 24.00 0 47 0 0
#> 31 24.00 0 36 0 1
#> 147.1 24.00 0 76 1 0
#> 172 24.00 0 41 0 0
#> 73 24.00 0 NA 0 1
#> 185 24.00 0 44 1 0
#> 119 24.00 0 17 0 0
#> 141 24.00 0 44 1 0
#> 147.2 24.00 0 76 1 0
#> 31.1 24.00 0 36 0 1
#> 71 24.00 0 51 0 0
#> 72.1 24.00 0 40 0 1
#> 141.1 24.00 0 44 1 0
#> 64 24.00 0 43 0 0
#> 73.1 24.00 0 NA 0 1
#> 53 24.00 0 32 0 1
#> 191 24.00 0 60 0 1
#> 3 24.00 0 31 1 0
#> 27 24.00 0 63 1 0
#> 98.1 24.00 0 34 1 0
#> 7.1 24.00 0 37 1 0
#> 146.1 24.00 0 63 1 0
#> 162 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 12 24.00 0 63 0 0
#> 115 24.00 0 NA 1 0
#> 72.2 24.00 0 40 0 1
#> 12.1 24.00 0 63 0 0
#> 152 24.00 0 36 0 1
#> 72.3 24.00 0 40 0 1
#> 44 24.00 0 56 0 0
#> 176 24.00 0 43 0 1
#> 11.1 24.00 0 42 0 1
#> 161.1 24.00 0 45 0 0
#> 191.1 24.00 0 60 0 1
#> 7.2 24.00 0 37 1 0
#> 144 24.00 0 28 0 1
#> 161.2 24.00 0 45 0 0
#> 83 24.00 0 6 0 0
#> 182 24.00 0 35 0 0
#> 112 24.00 0 61 0 0
#> 53.1 24.00 0 32 0 1
#> 148 24.00 0 61 1 0
#> 67 24.00 0 25 0 0
#> 131 24.00 0 66 0 0
#> 193 24.00 0 45 0 1
#> 103 24.00 0 56 1 0
#> 174.1 24.00 0 49 1 0
#> 102.1 24.00 0 49 0 0
#> 196 24.00 0 19 0 0
#> 151.1 24.00 0 42 0 0
#> 54.1 24.00 0 53 1 0
#> 121.1 24.00 0 57 1 0
#> 65.2 24.00 0 57 1 0
#> 174.2 24.00 0 49 1 0
#> 174.3 24.00 0 49 1 0
#> 191.2 24.00 0 60 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.01 NA NA NA
#> 2 age, Cure model 0.0224 NA NA NA
#> 3 grade_ii, Cure model -0.434 NA NA NA
#> 4 grade_iii, Cure model 0.743 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00336 NA NA NA
#> 2 grade_ii, Survival model 0.238 NA NA NA
#> 3 grade_iii, Survival model 0.178 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.00626 0.02235 -0.43361 0.74287
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.7
#> Residual Deviance: 242.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.00626071 0.02235227 -0.43361146 0.74286743
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003358758 0.238431705 0.177637238
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.429769109 0.792186462 0.468660202 0.890744150 0.429769109 0.091329979
#> [7] 0.380425380 0.292949392 0.026639702 0.498069350 0.312156949 0.050472655
#> [13] 0.351310269 0.498069350 0.292949392 0.604761261 0.950386188 0.634152882
#> [19] 0.130329308 0.351310269 0.226552770 0.478535109 0.634152882 0.565645750
#> [25] 0.565645750 0.713096041 0.831805901 0.026639702 0.149572365 0.226552770
#> [31] 0.458785381 0.331780535 0.910570283 0.168683358 0.110275436 0.419818359
#> [37] 0.399981213 0.546182546 0.546182546 0.380425380 0.990054536 0.960335426
#> [43] 0.604761261 0.187686376 0.351310269 0.091329979 0.653868259 0.070791565
#> [49] 0.130329308 0.831805901 0.683485501 0.812015565 0.920537580 0.149572365
#> [55] 0.831805901 0.890744150 0.321953496 0.015022738 0.080989733 0.498069350
#> [61] 0.742751060 0.004823159 0.273792341 0.120316230 0.207064164 0.970269475
#> [67] 0.409911121 0.970269475 0.060566604 0.930498584 0.812015565 0.245573453
#> [73] 0.498069350 0.594861061 0.792186462 0.216806227 0.752702050 0.604761261
#> [79] 0.565645750 0.273792341 0.026639702 0.245573453 0.653868259 0.197389944
#> [85] 0.831805901 0.168683358 0.331780535 0.713096041 0.693408004 0.245573453
#> [91] 0.732829671 0.673553039 0.693408004 0.752702050 0.772447558 0.870965543
#> [97] 0.429769109 0.478535109 0.772447558 0.536354435 0.870965543 0.940443094
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 106 56 130 10 106.1 63 41 97 86 5 179 168 51
#> 16.67 12.21 16.47 10.53 16.67 22.77 18.02 19.14 23.81 16.43 18.63 23.72 18.23
#> 5.1 97.1 6 16 39 197 51.1 170 85 39.1 100 100.1 155
#> 16.43 19.14 15.64 8.71 15.59 21.60 18.23 19.54 16.44 15.59 16.07 16.07 13.08
#> 43 86.1 153 170.1 171 88 93 99 175 23 184 188 188.1
#> 12.10 23.81 21.33 19.54 16.57 18.37 10.33 21.19 21.91 16.92 17.77 16.16 16.16
#> 41.1 127 70 6.1 190 51.2 63.1 167 92 197.1 43.1 96 49
#> 18.02 3.53 7.38 15.64 20.81 18.23 22.77 15.55 22.92 21.60 12.10 14.54 12.19
#> 61 153.1 43.2 10.1 8 78 113 5.2 177 24 76 136 150
#> 10.12 21.33 12.10 10.53 18.43 23.88 22.86 16.43 12.53 23.89 19.22 21.83 20.33
#> 77 117 77.1 164 101 49.1 55 5.3 26 56.1 158 37 6.2
#> 7.27 17.46 7.27 23.60 9.97 12.19 19.34 16.43 15.77 12.21 20.14 12.52 15.64
#> 100.2 76.1 86.2 58 167.1 128 43.3 99.1 88.1 155.1 57 55.1 123
#> 16.07 19.22 23.81 19.34 15.55 20.35 12.10 21.19 18.37 13.08 14.46 19.34 13.00
#> 180 57.1 37.1 42 107 106.2 192 42.1 79 107.1 183 80 74
#> 14.82 14.46 12.52 12.43 11.18 16.67 16.44 12.43 16.23 11.18 9.24 24.00 24.00
#> 151 165 143 121 186 72 116 65 9 138 98 62 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.1 174 1 22 87 11 160 102 147 74.1 146 38 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 161 132 21 31 147.1 172 185 119 141 147.2 31.1 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.1 141.1 64 53 191 3 27 98.1 7.1 146.1 162 17 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.2 12.1 152 72.3 44 176 11.1 161.1 191.1 7.2 144 161.2 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 112 53.1 148 67 131 193 103 174.1 102.1 196 151.1 54.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121.1 65.2 174.2 174.3 191.2
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[63]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004558345 1.005967513 0.395058144
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.35491228 -0.01060688 0.01609716
#> grade_iii, Cure model
#> 1.29626778
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 106 16.67 1 49 1 0
#> 167 15.55 1 56 1 0
#> 130 16.47 1 53 0 1
#> 187 9.92 1 39 1 0
#> 127 3.53 1 62 0 1
#> 179 18.63 1 42 0 0
#> 32 20.90 1 37 1 0
#> 139 21.49 1 63 1 0
#> 158 20.14 1 74 1 0
#> 127.1 3.53 1 62 0 1
#> 187.1 9.92 1 39 1 0
#> 14 12.89 1 21 0 0
#> 8 18.43 1 32 0 0
#> 169 22.41 1 46 0 0
#> 66 22.13 1 53 0 0
#> 26 15.77 1 49 0 1
#> 123 13.00 1 44 1 0
#> 175 21.91 1 43 0 0
#> 168 23.72 1 70 0 0
#> 13 14.34 1 54 0 1
#> 55 19.34 1 69 0 1
#> 123.1 13.00 1 44 1 0
#> 125 15.65 1 67 1 0
#> 133 14.65 1 57 0 0
#> 59 10.16 1 NA 1 0
#> 167.1 15.55 1 56 1 0
#> 60 13.15 1 38 1 0
#> 183 9.24 1 67 1 0
#> 166 19.98 1 48 0 0
#> 184 17.77 1 38 0 0
#> 169.1 22.41 1 46 0 0
#> 8.1 18.43 1 32 0 0
#> 59.1 10.16 1 NA 1 0
#> 127.2 3.53 1 62 0 1
#> 170 19.54 1 43 0 1
#> 133.1 14.65 1 57 0 0
#> 81 14.06 1 34 0 0
#> 61 10.12 1 36 0 1
#> 18 15.21 1 49 1 0
#> 159 10.55 1 50 0 1
#> 100 16.07 1 60 0 0
#> 5 16.43 1 51 0 1
#> 70 7.38 1 30 1 0
#> 99 21.19 1 38 0 1
#> 194 22.40 1 38 0 1
#> 130.1 16.47 1 53 0 1
#> 155 13.08 1 26 0 0
#> 14.1 12.89 1 21 0 0
#> 111 17.45 1 47 0 1
#> 108 18.29 1 39 0 1
#> 99.1 21.19 1 38 0 1
#> 88 18.37 1 47 0 0
#> 61.1 10.12 1 36 0 1
#> 88.1 18.37 1 47 0 0
#> 97 19.14 1 65 0 1
#> 93 10.33 1 52 0 1
#> 192 16.44 1 31 1 0
#> 117 17.46 1 26 0 1
#> 66.1 22.13 1 53 0 0
#> 107 11.18 1 54 1 0
#> 70.1 7.38 1 30 1 0
#> 69 23.23 1 25 0 1
#> 50 10.02 1 NA 1 0
#> 92 22.92 1 47 0 1
#> 26.1 15.77 1 49 0 1
#> 16 8.71 1 71 0 1
#> 145 10.07 1 65 1 0
#> 89 11.44 1 NA 0 0
#> 40 18.00 1 28 1 0
#> 128 20.35 1 35 0 1
#> 23 16.92 1 61 0 0
#> 179.1 18.63 1 42 0 0
#> 169.2 22.41 1 46 0 0
#> 43 12.10 1 61 0 1
#> 113 22.86 1 34 0 0
#> 127.3 3.53 1 62 0 1
#> 25 6.32 1 34 1 0
#> 23.1 16.92 1 61 0 0
#> 25.1 6.32 1 34 1 0
#> 145.1 10.07 1 65 1 0
#> 37 12.52 1 57 1 0
#> 89.1 11.44 1 NA 0 0
#> 57 14.46 1 45 0 1
#> 14.2 12.89 1 21 0 0
#> 150 20.33 1 48 0 0
#> 111.1 17.45 1 47 0 1
#> 66.2 22.13 1 53 0 0
#> 168.1 23.72 1 70 0 0
#> 10 10.53 1 34 0 0
#> 49 12.19 1 48 1 0
#> 56 12.21 1 60 0 0
#> 41 18.02 1 40 1 0
#> 61.2 10.12 1 36 0 1
#> 50.1 10.02 1 NA 1 0
#> 199 19.81 1 NA 0 1
#> 30 17.43 1 78 0 0
#> 13.1 14.34 1 54 0 1
#> 149 8.37 1 33 1 0
#> 130.2 16.47 1 53 0 1
#> 114 13.68 1 NA 0 0
#> 86 23.81 1 58 0 1
#> 60.1 13.15 1 38 1 0
#> 130.3 16.47 1 53 0 1
#> 177 12.53 1 75 0 0
#> 78 23.88 1 43 0 0
#> 99.2 21.19 1 38 0 1
#> 139.1 21.49 1 63 1 0
#> 4 17.64 1 NA 0 1
#> 89.2 11.44 1 NA 0 0
#> 41.1 18.02 1 40 1 0
#> 6 15.64 1 39 0 0
#> 117.1 17.46 1 26 0 1
#> 141 24.00 0 44 1 0
#> 131 24.00 0 66 0 0
#> 122 24.00 0 66 0 0
#> 146 24.00 0 63 1 0
#> 64 24.00 0 43 0 0
#> 131.1 24.00 0 66 0 0
#> 132 24.00 0 55 0 0
#> 80 24.00 0 41 0 0
#> 161 24.00 0 45 0 0
#> 75 24.00 0 21 1 0
#> 82 24.00 0 34 0 0
#> 83 24.00 0 6 0 0
#> 71 24.00 0 51 0 0
#> 200 24.00 0 64 0 0
#> 135 24.00 0 58 1 0
#> 1 24.00 0 23 1 0
#> 148 24.00 0 61 1 0
#> 120 24.00 0 68 0 1
#> 19 24.00 0 57 0 1
#> 119 24.00 0 17 0 0
#> 121 24.00 0 57 1 0
#> 163 24.00 0 66 0 0
#> 141.1 24.00 0 44 1 0
#> 80.1 24.00 0 41 0 0
#> 196 24.00 0 19 0 0
#> 34 24.00 0 36 0 0
#> 162 24.00 0 51 0 0
#> 161.1 24.00 0 45 0 0
#> 186 24.00 0 45 1 0
#> 163.1 24.00 0 66 0 0
#> 185 24.00 0 44 1 0
#> 135.1 24.00 0 58 1 0
#> 46 24.00 0 71 0 0
#> 163.2 24.00 0 66 0 0
#> 191 24.00 0 60 0 1
#> 115 24.00 0 NA 1 0
#> 148.1 24.00 0 61 1 0
#> 3 24.00 0 31 1 0
#> 185.1 24.00 0 44 1 0
#> 20 24.00 0 46 1 0
#> 9 24.00 0 31 1 0
#> 126 24.00 0 48 0 0
#> 131.2 24.00 0 66 0 0
#> 116 24.00 0 58 0 1
#> 11 24.00 0 42 0 1
#> 109 24.00 0 48 0 0
#> 46.1 24.00 0 71 0 0
#> 82.1 24.00 0 34 0 0
#> 1.1 24.00 0 23 1 0
#> 65 24.00 0 57 1 0
#> 94 24.00 0 51 0 1
#> 174 24.00 0 49 1 0
#> 163.3 24.00 0 66 0 0
#> 20.1 24.00 0 46 1 0
#> 120.1 24.00 0 68 0 1
#> 141.2 24.00 0 44 1 0
#> 28 24.00 0 67 1 0
#> 109.1 24.00 0 48 0 0
#> 67 24.00 0 25 0 0
#> 54 24.00 0 53 1 0
#> 75.1 24.00 0 21 1 0
#> 44 24.00 0 56 0 0
#> 17 24.00 0 38 0 1
#> 62 24.00 0 71 0 0
#> 35 24.00 0 51 0 0
#> 11.1 24.00 0 42 0 1
#> 143 24.00 0 51 0 0
#> 121.1 24.00 0 57 1 0
#> 165 24.00 0 47 0 0
#> 35.1 24.00 0 51 0 0
#> 143.1 24.00 0 51 0 0
#> 31 24.00 0 36 0 1
#> 186.1 24.00 0 45 1 0
#> 54.1 24.00 0 53 1 0
#> 95 24.00 0 68 0 1
#> 186.2 24.00 0 45 1 0
#> 44.1 24.00 0 56 0 0
#> 22 24.00 0 52 1 0
#> 104 24.00 0 50 1 0
#> 31.1 24.00 0 36 0 1
#> 182 24.00 0 35 0 0
#> 174.1 24.00 0 49 1 0
#> 20.2 24.00 0 46 1 0
#> 109.2 24.00 0 48 0 0
#> 162.1 24.00 0 51 0 0
#> 54.2 24.00 0 53 1 0
#> 44.2 24.00 0 56 0 0
#> 118 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.355 NA NA NA
#> 2 age, Cure model -0.0106 NA NA NA
#> 3 grade_ii, Cure model 0.0161 NA NA NA
#> 4 grade_iii, Cure model 1.30 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00456 NA NA NA
#> 2 grade_ii, Survival model 1.01 NA NA NA
#> 3 grade_iii, Survival model 0.395 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.35491 -0.01061 0.01610 1.29627
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 247 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.35491228 -0.01060688 0.01609716 1.29626778
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004558345 1.005967513 0.395058144
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.534148359 0.646186737 0.543855808 0.904586416 0.971595153 0.349775535
#> [7] 0.262150024 0.203724575 0.295723270 0.971595153 0.904586416 0.767171380
#> [13] 0.371164553 0.098408845 0.149863845 0.609307090 0.750680910 0.189336810
#> [19] 0.032361006 0.699019705 0.328246703 0.750680910 0.627805236 0.672674638
#> [25] 0.646186737 0.725228307 0.919861089 0.306541251 0.455779833 0.098408845
#> [31] 0.371164553 0.971595153 0.317434814 0.672674638 0.716446061 0.865224056
#> [37] 0.663898701 0.841066972 0.599933034 0.590593899 0.942584087 0.228011994
#> [43] 0.136219129 0.543855808 0.742156873 0.767171380 0.485294171 0.414511325
#> [49] 0.228011994 0.392722487 0.865224056 0.392722487 0.339028842 0.857176674
#> [55] 0.581228622 0.465777434 0.149863845 0.833003569 0.942584087 0.058123279
#> [61] 0.071775624 0.609307090 0.927466048 0.888971848 0.445816996 0.273393313
#> [67] 0.514489652 0.349775535 0.098408845 0.824850362 0.084940542 0.971595153
#> [73] 0.957237087 0.514489652 0.957237087 0.888971848 0.800183125 0.690216085
#> [79] 0.767171380 0.284515219 0.485294171 0.149863845 0.032361006 0.849116338
#> [85] 0.816687141 0.808425055 0.425481900 0.865224056 0.504656701 0.699019705
#> [91] 0.935066394 0.543855808 0.019436769 0.725228307 0.543855808 0.791845977
#> [97] 0.005758223 0.228011994 0.203724575 0.425481900 0.636985187 0.465777434
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 106 167 130 187 127 179 32 139 158 127.1 187.1 14 8
#> 16.67 15.55 16.47 9.92 3.53 18.63 20.90 21.49 20.14 3.53 9.92 12.89 18.43
#> 169 66 26 123 175 168 13 55 123.1 125 133 167.1 60
#> 22.41 22.13 15.77 13.00 21.91 23.72 14.34 19.34 13.00 15.65 14.65 15.55 13.15
#> 183 166 184 169.1 8.1 127.2 170 133.1 81 61 18 159 100
#> 9.24 19.98 17.77 22.41 18.43 3.53 19.54 14.65 14.06 10.12 15.21 10.55 16.07
#> 5 70 99 194 130.1 155 14.1 111 108 99.1 88 61.1 88.1
#> 16.43 7.38 21.19 22.40 16.47 13.08 12.89 17.45 18.29 21.19 18.37 10.12 18.37
#> 97 93 192 117 66.1 107 70.1 69 92 26.1 16 145 40
#> 19.14 10.33 16.44 17.46 22.13 11.18 7.38 23.23 22.92 15.77 8.71 10.07 18.00
#> 128 23 179.1 169.2 43 113 127.3 25 23.1 25.1 145.1 37 57
#> 20.35 16.92 18.63 22.41 12.10 22.86 3.53 6.32 16.92 6.32 10.07 12.52 14.46
#> 14.2 150 111.1 66.2 168.1 10 49 56 41 61.2 30 13.1 149
#> 12.89 20.33 17.45 22.13 23.72 10.53 12.19 12.21 18.02 10.12 17.43 14.34 8.37
#> 130.2 86 60.1 130.3 177 78 99.2 139.1 41.1 6 117.1 141 131
#> 16.47 23.81 13.15 16.47 12.53 23.88 21.19 21.49 18.02 15.64 17.46 24.00 24.00
#> 122 146 64 131.1 132 80 161 75 82 83 71 200 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 148 120 19 119 121 163 141.1 80.1 196 34 162 161.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 163.1 185 135.1 46 163.2 191 148.1 3 185.1 20 9 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.2 116 11 109 46.1 82.1 1.1 65 94 174 163.3 20.1 120.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141.2 28 109.1 67 54 75.1 44 17 62 35 11.1 143 121.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 35.1 143.1 31 186.1 54.1 95 186.2 44.1 22 104 31.1 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174.1 20.2 109.2 162.1 54.2 44.2 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[64]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002867337 0.569097966 0.532655203
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.15346854 0.00336150 0.03357578
#> grade_iii, Cure model
#> 0.42981508
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 10 10.53 1 34 0 0
#> 60 13.15 1 38 1 0
#> 42 12.43 1 49 0 1
#> 140 12.68 1 59 1 0
#> 111 17.45 1 47 0 1
#> 139 21.49 1 63 1 0
#> 36 21.19 1 48 0 1
#> 168 23.72 1 70 0 0
#> 43 12.10 1 61 0 1
#> 58 19.34 1 39 0 0
#> 192 16.44 1 31 1 0
#> 99 21.19 1 38 0 1
#> 85 16.44 1 36 0 0
#> 40 18.00 1 28 1 0
#> 23 16.92 1 61 0 0
#> 52 10.42 1 52 0 1
#> 86 23.81 1 58 0 1
#> 89 11.44 1 NA 0 0
#> 170 19.54 1 43 0 1
#> 189 10.51 1 NA 1 0
#> 99.1 21.19 1 38 0 1
#> 50 10.02 1 NA 1 0
#> 29 15.45 1 68 1 0
#> 66 22.13 1 53 0 0
#> 127 3.53 1 62 0 1
#> 61 10.12 1 36 0 1
#> 140.1 12.68 1 59 1 0
#> 187 9.92 1 39 1 0
#> 128 20.35 1 35 0 1
#> 13 14.34 1 54 0 1
#> 125 15.65 1 67 1 0
#> 51 18.23 1 83 0 1
#> 197 21.60 1 69 1 0
#> 16 8.71 1 71 0 1
#> 58.1 19.34 1 39 0 0
#> 14 12.89 1 21 0 0
#> 66.1 22.13 1 53 0 0
#> 187.1 9.92 1 39 1 0
#> 40.1 18.00 1 28 1 0
#> 188 16.16 1 46 0 1
#> 149 8.37 1 33 1 0
#> 105 19.75 1 60 0 0
#> 159 10.55 1 50 0 1
#> 181 16.46 1 45 0 1
#> 8 18.43 1 32 0 0
#> 8.1 18.43 1 32 0 0
#> 13.1 14.34 1 54 0 1
#> 59 10.16 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 184 17.77 1 38 0 0
#> 177 12.53 1 75 0 0
#> 113 22.86 1 34 0 0
#> 100.1 16.07 1 60 0 0
#> 68 20.62 1 44 0 0
#> 18 15.21 1 49 1 0
#> 129 23.41 1 53 1 0
#> 39 15.59 1 37 0 1
#> 123 13.00 1 44 1 0
#> 52.1 10.42 1 52 0 1
#> 30 17.43 1 78 0 0
#> 175 21.91 1 43 0 0
#> 14.1 12.89 1 21 0 0
#> 105.1 19.75 1 60 0 0
#> 124 9.73 1 NA 1 0
#> 199 19.81 1 NA 0 1
#> 155 13.08 1 26 0 0
#> 77 7.27 1 67 0 1
#> 39.1 15.59 1 37 0 1
#> 26 15.77 1 49 0 1
#> 166 19.98 1 48 0 0
#> 43.1 12.10 1 61 0 1
#> 23.1 16.92 1 61 0 0
#> 114 13.68 1 NA 0 0
#> 24 23.89 1 38 0 0
#> 106 16.67 1 49 1 0
#> 180 14.82 1 37 0 0
#> 85.1 16.44 1 36 0 0
#> 171 16.57 1 41 0 1
#> 124.1 9.73 1 NA 1 0
#> 113.1 22.86 1 34 0 0
#> 124.2 9.73 1 NA 1 0
#> 199.1 19.81 1 NA 0 1
#> 99.2 21.19 1 38 0 1
#> 194 22.40 1 38 0 1
#> 108 18.29 1 39 0 1
#> 139.1 21.49 1 63 1 0
#> 24.1 23.89 1 38 0 0
#> 101 9.97 1 10 0 1
#> 128.1 20.35 1 35 0 1
#> 57 14.46 1 45 0 1
#> 157 15.10 1 47 0 0
#> 167 15.55 1 56 1 0
#> 139.2 21.49 1 63 1 0
#> 114.1 13.68 1 NA 0 0
#> 13.2 14.34 1 54 0 1
#> 188.1 16.16 1 46 0 1
#> 8.2 18.43 1 32 0 0
#> 134 17.81 1 47 1 0
#> 190 20.81 1 42 1 0
#> 66.2 22.13 1 53 0 0
#> 180.1 14.82 1 37 0 0
#> 154 12.63 1 20 1 0
#> 5 16.43 1 51 0 1
#> 175.1 21.91 1 43 0 0
#> 130 16.47 1 53 0 1
#> 136 21.83 1 43 0 1
#> 183 9.24 1 67 1 0
#> 150 20.33 1 48 0 0
#> 133 14.65 1 57 0 0
#> 133.1 14.65 1 57 0 0
#> 184.1 17.77 1 38 0 0
#> 154.1 12.63 1 20 1 0
#> 116 24.00 0 58 0 1
#> 84 24.00 0 39 0 1
#> 94 24.00 0 51 0 1
#> 22 24.00 0 52 1 0
#> 74 24.00 0 43 0 1
#> 17 24.00 0 38 0 1
#> 162 24.00 0 51 0 0
#> 94.1 24.00 0 51 0 1
#> 148 24.00 0 61 1 0
#> 53 24.00 0 32 0 1
#> 148.1 24.00 0 61 1 0
#> 21 24.00 0 47 0 0
#> 47 24.00 0 38 0 1
#> 109 24.00 0 48 0 0
#> 67 24.00 0 25 0 0
#> 196 24.00 0 19 0 0
#> 67.1 24.00 0 25 0 0
#> 120 24.00 0 68 0 1
#> 65 24.00 0 57 1 0
#> 135 24.00 0 58 1 0
#> 165 24.00 0 47 0 0
#> 173 24.00 0 19 0 1
#> 31 24.00 0 36 0 1
#> 172 24.00 0 41 0 0
#> 131 24.00 0 66 0 0
#> 33 24.00 0 53 0 0
#> 142 24.00 0 53 0 0
#> 122 24.00 0 66 0 0
#> 118 24.00 0 44 1 0
#> 126 24.00 0 48 0 0
#> 163 24.00 0 66 0 0
#> 178 24.00 0 52 1 0
#> 120.1 24.00 0 68 0 1
#> 172.1 24.00 0 41 0 0
#> 22.1 24.00 0 52 1 0
#> 28 24.00 0 67 1 0
#> 2 24.00 0 9 0 0
#> 196.1 24.00 0 19 0 0
#> 109.1 24.00 0 48 0 0
#> 165.1 24.00 0 47 0 0
#> 165.2 24.00 0 47 0 0
#> 34 24.00 0 36 0 0
#> 47.1 24.00 0 38 0 1
#> 84.1 24.00 0 39 0 1
#> 44 24.00 0 56 0 0
#> 162.1 24.00 0 51 0 0
#> 46 24.00 0 71 0 0
#> 115 24.00 0 NA 1 0
#> 35 24.00 0 51 0 0
#> 163.1 24.00 0 66 0 0
#> 34.1 24.00 0 36 0 0
#> 135.1 24.00 0 58 1 0
#> 95 24.00 0 68 0 1
#> 156 24.00 0 50 1 0
#> 95.1 24.00 0 68 0 1
#> 160 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 121 24.00 0 57 1 0
#> 80 24.00 0 41 0 0
#> 62 24.00 0 71 0 0
#> 185 24.00 0 44 1 0
#> 33.1 24.00 0 53 0 0
#> 38 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 64 24.00 0 43 0 0
#> 21.1 24.00 0 47 0 0
#> 176 24.00 0 43 0 1
#> 1.1 24.00 0 23 1 0
#> 131.1 24.00 0 66 0 0
#> 7 24.00 0 37 1 0
#> 7.1 24.00 0 37 1 0
#> 2.1 24.00 0 9 0 0
#> 17.1 24.00 0 38 0 1
#> 146 24.00 0 63 1 0
#> 47.2 24.00 0 38 0 1
#> 176.1 24.00 0 43 0 1
#> 2.2 24.00 0 9 0 0
#> 160.1 24.00 0 31 1 0
#> 44.1 24.00 0 56 0 0
#> 17.2 24.00 0 38 0 1
#> 146.1 24.00 0 63 1 0
#> 12 24.00 0 63 0 0
#> 34.2 24.00 0 36 0 0
#> 193 24.00 0 45 0 1
#> 173.1 24.00 0 19 0 1
#> 112 24.00 0 61 0 0
#> 191 24.00 0 60 0 1
#> 22.2 24.00 0 52 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.153 NA NA NA
#> 2 age, Cure model 0.00336 NA NA NA
#> 3 grade_ii, Cure model 0.0336 NA NA NA
#> 4 grade_iii, Cure model 0.430 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00287 NA NA NA
#> 2 grade_ii, Survival model 0.569 NA NA NA
#> 3 grade_iii, Survival model 0.533 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.153469 0.003361 0.033576 0.429815
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.6
#> Residual Deviance: 257.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.15346854 0.00336150 0.03357578 0.42981508
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002867337 0.569097966 0.532655203
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.90456246 0.78792421 0.87181806 0.83031292 0.49953966 0.21575480
#> [7] 0.24951142 0.05590748 0.88008197 0.38131715 0.57573042 0.24951142
#> [13] 0.57573042 0.45147016 0.51873484 0.91273078 0.04104521 0.37119443
#> [19] 0.24951142 0.69285952 0.12556319 0.99220655 0.92885997 0.83031292
#> [25] 0.94493916 0.31074123 0.76249231 0.65745939 0.44145093 0.20285015
#> [31] 0.96865869 0.38131715 0.81343549 0.12556319 0.94493916 0.45147016
#> [37] 0.61232147 0.97654204 0.35094968 0.89640099 0.56638954 0.40140542
#> [43] 0.40140542 0.76249231 0.63032644 0.48038672 0.86351638 0.08561296
#> [49] 0.63032644 0.30026300 0.70161246 0.07154735 0.66644903 0.80496287
#> [55] 0.91273078 0.50911912 0.16302311 0.81343549 0.35094968 0.79644027
#> [61] 0.98438694 0.66644903 0.64841310 0.34077130 0.88008197 0.51873484
#> [67] 0.01345778 0.53790106 0.71901570 0.57573042 0.54747897 0.08561296
#> [73] 0.24951142 0.11223788 0.43135317 0.21575480 0.01345778 0.93692217
#> [79] 0.31074123 0.75378415 0.71030736 0.68405613 0.21575480 0.76249231
#> [85] 0.61232147 0.40140542 0.47075295 0.28982797 0.12556319 0.71901570
#> [91] 0.84702335 0.60311742 0.16302311 0.55697143 0.18956602 0.96075027
#> [97] 0.33063188 0.73636898 0.73636898 0.48038672 0.84702335 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 10 60 42 140 111 139 36 168 43 58 192 99 85
#> 10.53 13.15 12.43 12.68 17.45 21.49 21.19 23.72 12.10 19.34 16.44 21.19 16.44
#> 40 23 52 86 170 99.1 29 66 127 61 140.1 187 128
#> 18.00 16.92 10.42 23.81 19.54 21.19 15.45 22.13 3.53 10.12 12.68 9.92 20.35
#> 13 125 51 197 16 58.1 14 66.1 187.1 40.1 188 149 105
#> 14.34 15.65 18.23 21.60 8.71 19.34 12.89 22.13 9.92 18.00 16.16 8.37 19.75
#> 159 181 8 8.1 13.1 100 184 177 113 100.1 68 18 129
#> 10.55 16.46 18.43 18.43 14.34 16.07 17.77 12.53 22.86 16.07 20.62 15.21 23.41
#> 39 123 52.1 30 175 14.1 105.1 155 77 39.1 26 166 43.1
#> 15.59 13.00 10.42 17.43 21.91 12.89 19.75 13.08 7.27 15.59 15.77 19.98 12.10
#> 23.1 24 106 180 85.1 171 113.1 99.2 194 108 139.1 24.1 101
#> 16.92 23.89 16.67 14.82 16.44 16.57 22.86 21.19 22.40 18.29 21.49 23.89 9.97
#> 128.1 57 157 167 139.2 13.2 188.1 8.2 134 190 66.2 180.1 154
#> 20.35 14.46 15.10 15.55 21.49 14.34 16.16 18.43 17.81 20.81 22.13 14.82 12.63
#> 5 175.1 130 136 183 150 133 133.1 184.1 154.1 116 84 94
#> 16.43 21.91 16.47 21.83 9.24 20.33 14.65 14.65 17.77 12.63 24.00 24.00 24.00
#> 22 74 17 162 94.1 148 53 148.1 21 47 109 67 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67.1 120 65 135 165 173 31 172 131 33 142 122 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 163 178 120.1 172.1 22.1 28 2 196.1 109.1 165.1 165.2 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47.1 84.1 44 162.1 46 35 163.1 34.1 135.1 95 156 95.1 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 121 80 62 185 33.1 38 1 64 21.1 176 1.1 131.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 7.1 2.1 17.1 146 47.2 176.1 2.2 160.1 44.1 17.2 146.1 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34.2 193 173.1 112 191 22.2
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[65]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00292058 0.54430474 0.28486045
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.55424476 0.01157068 -0.36123798
#> grade_iii, Cure model
#> 1.14629107
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 51 18.23 1 83 0 1
#> 24 23.89 1 38 0 0
#> 157 15.10 1 47 0 0
#> 159 10.55 1 50 0 1
#> 58 19.34 1 39 0 0
#> 55 19.34 1 69 0 1
#> 159.1 10.55 1 50 0 1
#> 155 13.08 1 26 0 0
#> 69 23.23 1 25 0 1
#> 61 10.12 1 36 0 1
#> 189 10.51 1 NA 1 0
#> 93 10.33 1 52 0 1
#> 96 14.54 1 33 0 1
#> 86 23.81 1 58 0 1
#> 190 20.81 1 42 1 0
#> 190.1 20.81 1 42 1 0
#> 77 7.27 1 67 0 1
#> 155.1 13.08 1 26 0 0
#> 4 17.64 1 NA 0 1
#> 88 18.37 1 47 0 0
#> 134 17.81 1 47 1 0
#> 96.1 14.54 1 33 0 1
#> 70 7.38 1 30 1 0
#> 177 12.53 1 75 0 0
#> 167 15.55 1 56 1 0
#> 169 22.41 1 46 0 0
#> 197 21.60 1 69 1 0
#> 63 22.77 1 31 1 0
#> 117 17.46 1 26 0 1
#> 88.1 18.37 1 47 0 0
#> 89 11.44 1 NA 0 0
#> 92 22.92 1 47 0 1
#> 123 13.00 1 44 1 0
#> 5 16.43 1 51 0 1
#> 125 15.65 1 67 1 0
#> 177.1 12.53 1 75 0 0
#> 181 16.46 1 45 0 1
#> 36 21.19 1 48 0 1
#> 108 18.29 1 39 0 1
#> 134.1 17.81 1 47 1 0
#> 92.1 22.92 1 47 0 1
#> 78 23.88 1 43 0 0
#> 101 9.97 1 10 0 1
#> 58.1 19.34 1 39 0 0
#> 81 14.06 1 34 0 0
#> 197.1 21.60 1 69 1 0
#> 197.2 21.60 1 69 1 0
#> 43 12.10 1 61 0 1
#> 6 15.64 1 39 0 0
#> 167.1 15.55 1 56 1 0
#> 108.1 18.29 1 39 0 1
#> 155.2 13.08 1 26 0 0
#> 184 17.77 1 38 0 0
#> 164 23.60 1 76 0 1
#> 36.1 21.19 1 48 0 1
#> 16 8.71 1 71 0 1
#> 29 15.45 1 68 1 0
#> 15 22.68 1 48 0 0
#> 61.1 10.12 1 36 0 1
#> 6.1 15.64 1 39 0 0
#> 100 16.07 1 60 0 0
#> 117.1 17.46 1 26 0 1
#> 5.1 16.43 1 51 0 1
#> 113 22.86 1 34 0 0
#> 195 11.76 1 NA 1 0
#> 128 20.35 1 35 0 1
#> 6.2 15.64 1 39 0 0
#> 59 10.16 1 NA 1 0
#> 158 20.14 1 74 1 0
#> 13 14.34 1 54 0 1
#> 5.2 16.43 1 51 0 1
#> 36.2 21.19 1 48 0 1
#> 168 23.72 1 70 0 0
#> 136 21.83 1 43 0 1
#> 51.1 18.23 1 83 0 1
#> 111 17.45 1 47 0 1
#> 145 10.07 1 65 1 0
#> 88.2 18.37 1 47 0 0
#> 188 16.16 1 46 0 1
#> 13.1 14.34 1 54 0 1
#> 32 20.90 1 37 1 0
#> 56 12.21 1 60 0 0
#> 145.1 10.07 1 65 1 0
#> 58.2 19.34 1 39 0 0
#> 140 12.68 1 59 1 0
#> 88.3 18.37 1 47 0 0
#> 145.2 10.07 1 65 1 0
#> 194 22.40 1 38 0 1
#> 50 10.02 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 49 12.19 1 48 1 0
#> 6.3 15.64 1 39 0 0
#> 157.1 15.10 1 47 0 0
#> 24.1 23.89 1 38 0 0
#> 79 16.23 1 54 1 0
#> 183 9.24 1 67 1 0
#> 180 14.82 1 37 0 0
#> 50.1 10.02 1 NA 1 0
#> 58.3 19.34 1 39 0 0
#> 154 12.63 1 20 1 0
#> 45 17.42 1 54 0 1
#> 168.1 23.72 1 70 0 0
#> 187 9.92 1 39 1 0
#> 153 21.33 1 55 1 0
#> 133 14.65 1 57 0 0
#> 101.1 9.97 1 10 0 1
#> 23 16.92 1 61 0 0
#> 125.1 15.65 1 67 1 0
#> 110 17.56 1 65 0 1
#> 181.1 16.46 1 45 0 1
#> 181.2 16.46 1 45 0 1
#> 194.1 22.40 1 38 0 1
#> 46 24.00 0 71 0 0
#> 200 24.00 0 64 0 0
#> 151 24.00 0 42 0 0
#> 48 24.00 0 31 1 0
#> 200.1 24.00 0 64 0 0
#> 48.1 24.00 0 31 1 0
#> 82 24.00 0 34 0 0
#> 118 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 65 24.00 0 57 1 0
#> 64 24.00 0 43 0 0
#> 143 24.00 0 51 0 0
#> 87 24.00 0 27 0 0
#> 87.1 24.00 0 27 0 0
#> 62 24.00 0 71 0 0
#> 174 24.00 0 49 1 0
#> 156 24.00 0 50 1 0
#> 163 24.00 0 66 0 0
#> 137 24.00 0 45 1 0
#> 119 24.00 0 17 0 0
#> 11 24.00 0 42 0 1
#> 137.1 24.00 0 45 1 0
#> 7 24.00 0 37 1 0
#> 146 24.00 0 63 1 0
#> 138 24.00 0 44 1 0
#> 98 24.00 0 34 1 0
#> 151.1 24.00 0 42 0 0
#> 146.1 24.00 0 63 1 0
#> 120 24.00 0 68 0 1
#> 46.1 24.00 0 71 0 0
#> 141 24.00 0 44 1 0
#> 20 24.00 0 46 1 0
#> 116 24.00 0 58 0 1
#> 44 24.00 0 56 0 0
#> 28 24.00 0 67 1 0
#> 65.1 24.00 0 57 1 0
#> 173 24.00 0 19 0 1
#> 104 24.00 0 50 1 0
#> 186 24.00 0 45 1 0
#> 54 24.00 0 53 1 0
#> 17 24.00 0 38 0 1
#> 1 24.00 0 23 1 0
#> 112.1 24.00 0 61 0 0
#> 152 24.00 0 36 0 1
#> 75 24.00 0 21 1 0
#> 104.1 24.00 0 50 1 0
#> 98.1 24.00 0 34 1 0
#> 72 24.00 0 40 0 1
#> 144 24.00 0 28 0 1
#> 31 24.00 0 36 0 1
#> 132 24.00 0 55 0 0
#> 115 24.00 0 NA 1 0
#> 11.1 24.00 0 42 0 1
#> 54.1 24.00 0 53 1 0
#> 1.1 24.00 0 23 1 0
#> 65.2 24.00 0 57 1 0
#> 178 24.00 0 52 1 0
#> 34 24.00 0 36 0 0
#> 148 24.00 0 61 1 0
#> 142 24.00 0 53 0 0
#> 34.1 24.00 0 36 0 0
#> 35 24.00 0 51 0 0
#> 131 24.00 0 66 0 0
#> 95 24.00 0 68 0 1
#> 27 24.00 0 63 1 0
#> 53 24.00 0 32 0 1
#> 54.2 24.00 0 53 1 0
#> 137.2 24.00 0 45 1 0
#> 44.1 24.00 0 56 0 0
#> 48.2 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 193 24.00 0 45 0 1
#> 165 24.00 0 47 0 0
#> 95.1 24.00 0 68 0 1
#> 103 24.00 0 56 1 0
#> 38 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 185.1 24.00 0 44 1 0
#> 71 24.00 0 51 0 0
#> 35.1 24.00 0 51 0 0
#> 161.1 24.00 0 45 0 0
#> 82.1 24.00 0 34 0 0
#> 27.1 24.00 0 63 1 0
#> 112.2 24.00 0 61 0 0
#> 34.2 24.00 0 36 0 0
#> 162 24.00 0 51 0 0
#> 46.2 24.00 0 71 0 0
#> 83 24.00 0 6 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.554 NA NA NA
#> 2 age, Cure model 0.0116 NA NA NA
#> 3 grade_ii, Cure model -0.361 NA NA NA
#> 4 grade_iii, Cure model 1.15 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00292 NA NA NA
#> 2 grade_ii, Survival model 0.544 NA NA NA
#> 3 grade_iii, Survival model 0.285 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.55424 0.01157 -0.36124 1.14629
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.5
#> Residual Deviance: 247.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.55424476 0.01157068 -0.36123798 1.14629107
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00292058 0.54430474 0.28486045
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.429529782 0.009467194 0.699820466 0.873802469 0.328517416 0.328517416
#> [7] 0.873802469 0.778542474 0.092371965 0.899502040 0.890915714 0.734932311
#> [13] 0.042075863 0.290461663 0.290461663 0.991716372 0.778542474 0.373674533
#> [19] 0.448296796 0.734932311 0.983426285 0.830629028 0.673535418 0.164064024
#> [25] 0.209896710 0.140574154 0.485263500 0.373674533 0.105137308 0.804586808
#> [31] 0.567202919 0.620903822 0.830629028 0.540265639 0.250942896 0.410727278
#> [37] 0.448296796 0.105137308 0.028939499 0.941654161 0.328517416 0.769784078
#> [43] 0.209896710 0.209896710 0.865178262 0.638541527 0.673535418 0.410727278
#> [49] 0.778542474 0.466677426 0.079180204 0.250942896 0.975095549 0.691052098
#> [55] 0.152259642 0.899502040 0.638541527 0.611914170 0.485263500 0.567202919
#> [61] 0.128303935 0.309454326 0.638541527 0.319041161 0.752385545 0.567202919
#> [67] 0.250942896 0.054763742 0.198441838 0.429529782 0.503493447 0.916529048
#> [73] 0.373674533 0.602945698 0.752385545 0.280456152 0.847866912 0.916529048
#> [79] 0.328517416 0.813314561 0.373674533 0.916529048 0.175976481 0.512665809
#> [85] 0.856544365 0.638541527 0.699820466 0.009467194 0.593955509 0.966759074
#> [91] 0.717303200 0.328517416 0.822000315 0.521871728 0.054763742 0.958392507
#> [97] 0.240494310 0.726109550 0.941654161 0.531055686 0.620903822 0.475979503
#> [103] 0.540265639 0.540265639 0.175976481 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 51 24 157 159 58 55 159.1 155 69 61 93 96 86
#> 18.23 23.89 15.10 10.55 19.34 19.34 10.55 13.08 23.23 10.12 10.33 14.54 23.81
#> 190 190.1 77 155.1 88 134 96.1 70 177 167 169 197 63
#> 20.81 20.81 7.27 13.08 18.37 17.81 14.54 7.38 12.53 15.55 22.41 21.60 22.77
#> 117 88.1 92 123 5 125 177.1 181 36 108 134.1 92.1 78
#> 17.46 18.37 22.92 13.00 16.43 15.65 12.53 16.46 21.19 18.29 17.81 22.92 23.88
#> 101 58.1 81 197.1 197.2 43 6 167.1 108.1 155.2 184 164 36.1
#> 9.97 19.34 14.06 21.60 21.60 12.10 15.64 15.55 18.29 13.08 17.77 23.60 21.19
#> 16 29 15 61.1 6.1 100 117.1 5.1 113 128 6.2 158 13
#> 8.71 15.45 22.68 10.12 15.64 16.07 17.46 16.43 22.86 20.35 15.64 20.14 14.34
#> 5.2 36.2 168 136 51.1 111 145 88.2 188 13.1 32 56 145.1
#> 16.43 21.19 23.72 21.83 18.23 17.45 10.07 18.37 16.16 14.34 20.90 12.21 10.07
#> 58.2 140 88.3 145.2 194 30 49 6.3 157.1 24.1 79 183 180
#> 19.34 12.68 18.37 10.07 22.40 17.43 12.19 15.64 15.10 23.89 16.23 9.24 14.82
#> 58.3 154 45 168.1 187 153 133 101.1 23 125.1 110 181.1 181.2
#> 19.34 12.63 17.42 23.72 9.92 21.33 14.65 9.97 16.92 15.65 17.56 16.46 16.46
#> 194.1 46 200 151 48 200.1 48.1 82 118 112 65 64 143
#> 22.40 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 87.1 62 174 156 163 137 119 11 137.1 7 146 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 151.1 146.1 120 46.1 141 20 116 44 28 65.1 173 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 54 17 1 112.1 152 75 104.1 98.1 72 144 31 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11.1 54.1 1.1 65.2 178 34 148 142 34.1 35 131 95 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 54.2 137.2 44.1 48.2 161 193 165 95.1 103 38 185 185.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 35.1 161.1 82.1 27.1 112.2 34.2 162 46.2 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[66]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0004705521 0.8282932605 0.6614145269
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.290941787 0.009260043 0.133071421
#> grade_iii, Cure model
#> 0.166114674
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 25 6.32 1 34 1 0
#> 105 19.75 1 60 0 0
#> 136 21.83 1 43 0 1
#> 177 12.53 1 75 0 0
#> 155 13.08 1 26 0 0
#> 68 20.62 1 44 0 0
#> 81 14.06 1 34 0 0
#> 106 16.67 1 49 1 0
#> 107 11.18 1 54 1 0
#> 175 21.91 1 43 0 0
#> 5 16.43 1 51 0 1
#> 149 8.37 1 33 1 0
#> 169 22.41 1 46 0 0
#> 79 16.23 1 54 1 0
#> 59 10.16 1 NA 1 0
#> 61 10.12 1 36 0 1
#> 77 7.27 1 67 0 1
#> 128 20.35 1 35 0 1
#> 177.1 12.53 1 75 0 0
#> 13 14.34 1 54 0 1
#> 184 17.77 1 38 0 0
#> 105.1 19.75 1 60 0 0
#> 145 10.07 1 65 1 0
#> 113 22.86 1 34 0 0
#> 168 23.72 1 70 0 0
#> 166 19.98 1 48 0 0
#> 181 16.46 1 45 0 1
#> 192 16.44 1 31 1 0
#> 130 16.47 1 53 0 1
#> 79.1 16.23 1 54 1 0
#> 90 20.94 1 50 0 1
#> 129 23.41 1 53 1 0
#> 89 11.44 1 NA 0 0
#> 63 22.77 1 31 1 0
#> 117 17.46 1 26 0 1
#> 6 15.64 1 39 0 0
#> 180 14.82 1 37 0 0
#> 106.1 16.67 1 49 1 0
#> 30 17.43 1 78 0 0
#> 140 12.68 1 59 1 0
#> 127 3.53 1 62 0 1
#> 58 19.34 1 39 0 0
#> 145.1 10.07 1 65 1 0
#> 16 8.71 1 71 0 1
#> 78 23.88 1 43 0 0
#> 159 10.55 1 50 0 1
#> 23 16.92 1 61 0 0
#> 124 9.73 1 NA 1 0
#> 92 22.92 1 47 0 1
#> 15 22.68 1 48 0 0
#> 181.1 16.46 1 45 0 1
#> 110 17.56 1 65 0 1
#> 57 14.46 1 45 0 1
#> 59.1 10.16 1 NA 1 0
#> 133 14.65 1 57 0 0
#> 6.1 15.64 1 39 0 0
#> 123 13.00 1 44 1 0
#> 57.1 14.46 1 45 0 1
#> 107.1 11.18 1 54 1 0
#> 187 9.92 1 39 1 0
#> 149.1 8.37 1 33 1 0
#> 45 17.42 1 54 0 1
#> 97 19.14 1 65 0 1
#> 145.2 10.07 1 65 1 0
#> 25.1 6.32 1 34 1 0
#> 111 17.45 1 47 0 1
#> 69 23.23 1 25 0 1
#> 190 20.81 1 42 1 0
#> 105.2 19.75 1 60 0 0
#> 175.1 21.91 1 43 0 0
#> 89.1 11.44 1 NA 0 0
#> 79.2 16.23 1 54 1 0
#> 180.1 14.82 1 37 0 0
#> 188 16.16 1 46 0 1
#> 157 15.10 1 47 0 0
#> 101 9.97 1 10 0 1
#> 134 17.81 1 47 1 0
#> 158 20.14 1 74 1 0
#> 15.1 22.68 1 48 0 0
#> 61.1 10.12 1 36 0 1
#> 168.1 23.72 1 70 0 0
#> 105.3 19.75 1 60 0 0
#> 25.2 6.32 1 34 1 0
#> 153 21.33 1 55 1 0
#> 133.1 14.65 1 57 0 0
#> 81.1 14.06 1 34 0 0
#> 99 21.19 1 38 0 1
#> 57.2 14.46 1 45 0 1
#> 107.2 11.18 1 54 1 0
#> 127.1 3.53 1 62 0 1
#> 184.1 17.77 1 38 0 0
#> 51 18.23 1 83 0 1
#> 189 10.51 1 NA 1 0
#> 58.1 19.34 1 39 0 0
#> 76 19.22 1 54 0 1
#> 32 20.90 1 37 1 0
#> 155.1 13.08 1 26 0 0
#> 140.1 12.68 1 59 1 0
#> 158.1 20.14 1 74 1 0
#> 24 23.89 1 38 0 0
#> 168.2 23.72 1 70 0 0
#> 145.3 10.07 1 65 1 0
#> 150 20.33 1 48 0 0
#> 106.2 16.67 1 49 1 0
#> 171 16.57 1 41 0 1
#> 159.1 10.55 1 50 0 1
#> 168.3 23.72 1 70 0 0
#> 117.1 17.46 1 26 0 1
#> 8 18.43 1 32 0 0
#> 99.1 21.19 1 38 0 1
#> 57.3 14.46 1 45 0 1
#> 100 16.07 1 60 0 0
#> 71 24.00 0 51 0 0
#> 34 24.00 0 36 0 0
#> 98 24.00 0 34 1 0
#> 46 24.00 0 71 0 0
#> 34.1 24.00 0 36 0 0
#> 9 24.00 0 31 1 0
#> 115 24.00 0 NA 1 0
#> 34.2 24.00 0 36 0 0
#> 71.1 24.00 0 51 0 0
#> 163 24.00 0 66 0 0
#> 147 24.00 0 76 1 0
#> 11 24.00 0 42 0 1
#> 165 24.00 0 47 0 0
#> 47 24.00 0 38 0 1
#> 116 24.00 0 58 0 1
#> 9.1 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 147.1 24.00 0 76 1 0
#> 109.1 24.00 0 48 0 0
#> 75 24.00 0 21 1 0
#> 34.3 24.00 0 36 0 0
#> 112 24.00 0 61 0 0
#> 143 24.00 0 51 0 0
#> 121 24.00 0 57 1 0
#> 54 24.00 0 53 1 0
#> 65 24.00 0 57 1 0
#> 115.1 24.00 0 NA 1 0
#> 94 24.00 0 51 0 1
#> 21 24.00 0 47 0 0
#> 144 24.00 0 28 0 1
#> 33 24.00 0 53 0 0
#> 142 24.00 0 53 0 0
#> 46.1 24.00 0 71 0 0
#> 103 24.00 0 56 1 0
#> 135 24.00 0 58 1 0
#> 109.2 24.00 0 48 0 0
#> 87 24.00 0 27 0 0
#> 142.1 24.00 0 53 0 0
#> 165.1 24.00 0 47 0 0
#> 12 24.00 0 63 0 0
#> 31 24.00 0 36 0 1
#> 146 24.00 0 63 1 0
#> 21.1 24.00 0 47 0 0
#> 11.1 24.00 0 42 0 1
#> 72 24.00 0 40 0 1
#> 65.1 24.00 0 57 1 0
#> 198 24.00 0 66 0 1
#> 84 24.00 0 39 0 1
#> 11.2 24.00 0 42 0 1
#> 35 24.00 0 51 0 0
#> 33.1 24.00 0 53 0 0
#> 19 24.00 0 57 0 1
#> 115.2 24.00 0 NA 1 0
#> 19.1 24.00 0 57 0 1
#> 53 24.00 0 32 0 1
#> 80 24.00 0 41 0 0
#> 151 24.00 0 42 0 0
#> 75.1 24.00 0 21 1 0
#> 115.3 24.00 0 NA 1 0
#> 31.1 24.00 0 36 0 1
#> 7 24.00 0 37 1 0
#> 191 24.00 0 60 0 1
#> 104 24.00 0 50 1 0
#> 47.1 24.00 0 38 0 1
#> 182 24.00 0 35 0 0
#> 67 24.00 0 25 0 0
#> 144.1 24.00 0 28 0 1
#> 19.2 24.00 0 57 0 1
#> 87.1 24.00 0 27 0 0
#> 103.1 24.00 0 56 1 0
#> 163.1 24.00 0 66 0 0
#> 20 24.00 0 46 1 0
#> 103.2 24.00 0 56 1 0
#> 31.2 24.00 0 36 0 1
#> 151.1 24.00 0 42 0 0
#> 115.4 24.00 0 NA 1 0
#> 12.1 24.00 0 63 0 0
#> 7.1 24.00 0 37 1 0
#> 74 24.00 0 43 0 1
#> 163.2 24.00 0 66 0 0
#> 53.1 24.00 0 32 0 1
#> 138 24.00 0 44 1 0
#> 120 24.00 0 68 0 1
#> 173 24.00 0 19 0 1
#> 74.1 24.00 0 43 0 1
#> 185 24.00 0 44 1 0
#> 146.1 24.00 0 63 1 0
#> 193 24.00 0 45 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.291 NA NA NA
#> 2 age, Cure model 0.00926 NA NA NA
#> 3 grade_ii, Cure model 0.133 NA NA NA
#> 4 grade_iii, Cure model 0.166 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000471 NA NA NA
#> 2 grade_ii, Survival model 0.828 NA NA NA
#> 3 grade_iii, Survival model 0.661 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.29094 0.00926 0.13307 0.16611
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 259.2
#> Residual Deviance: 258.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.290941787 0.009260043 0.133071421 0.166114674
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0004705521 0.8282932605 0.6614145269
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.97142368 0.43140904 0.28812126 0.85290142 0.81893419 0.37085916
#> [7] 0.80517119 0.61424172 0.86626903 0.26071582 0.67712675 0.95370356
#> [13] 0.24666455 0.68468060 0.89851917 0.96552602 0.38151151 0.85290142
#> [19] 0.79826191 0.53563323 0.43140904 0.91118350 0.18998741 0.07030048
#> [25] 0.42162600 0.65410538 0.66949700 0.64619584 0.68468060 0.33765275
#> [31] 0.13957116 0.20535075 0.56268799 0.72060516 0.74211619 0.61424172
#> [37] 0.58861568 0.83954107 0.98861940 0.46932469 0.91118350 0.94767995
#> [43] 0.04223119 0.88569123 0.60573379 0.17464444 0.21939511 0.65410538
#> [49] 0.55370638 0.77077279 0.75644089 0.72060516 0.83270002 0.77077279
#> [55] 0.86626903 0.94162271 0.95370356 0.59722925 0.49830905 0.91118350
#> [61] 0.97142368 0.58000664 0.15799400 0.36021311 0.43140904 0.26071582
#> [67] 0.68468060 0.74211619 0.70622440 0.73492135 0.93551645 0.52652464
#> [73] 0.40229686 0.21939511 0.89851917 0.07030048 0.43140904 0.97142368
#> [79] 0.30157704 0.75644089 0.80517119 0.31433248 0.77077279 0.86626903
#> [85] 0.98861940 0.53563323 0.51721649 0.46932469 0.48869634 0.34916055
#> [91] 0.81893419 0.83954107 0.40229686 0.01525820 0.07030048 0.91118350
#> [97] 0.39190110 0.61424172 0.63819920 0.88569123 0.07030048 0.56268799
#> [103] 0.50776145 0.31433248 0.77077279 0.71341377 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 25 105 136 177 155 68 81 106 107 175 5 149 169
#> 6.32 19.75 21.83 12.53 13.08 20.62 14.06 16.67 11.18 21.91 16.43 8.37 22.41
#> 79 61 77 128 177.1 13 184 105.1 145 113 168 166 181
#> 16.23 10.12 7.27 20.35 12.53 14.34 17.77 19.75 10.07 22.86 23.72 19.98 16.46
#> 192 130 79.1 90 129 63 117 6 180 106.1 30 140 127
#> 16.44 16.47 16.23 20.94 23.41 22.77 17.46 15.64 14.82 16.67 17.43 12.68 3.53
#> 58 145.1 16 78 159 23 92 15 181.1 110 57 133 6.1
#> 19.34 10.07 8.71 23.88 10.55 16.92 22.92 22.68 16.46 17.56 14.46 14.65 15.64
#> 123 57.1 107.1 187 149.1 45 97 145.2 25.1 111 69 190 105.2
#> 13.00 14.46 11.18 9.92 8.37 17.42 19.14 10.07 6.32 17.45 23.23 20.81 19.75
#> 175.1 79.2 180.1 188 157 101 134 158 15.1 61.1 168.1 105.3 25.2
#> 21.91 16.23 14.82 16.16 15.10 9.97 17.81 20.14 22.68 10.12 23.72 19.75 6.32
#> 153 133.1 81.1 99 57.2 107.2 127.1 184.1 51 58.1 76 32 155.1
#> 21.33 14.65 14.06 21.19 14.46 11.18 3.53 17.77 18.23 19.34 19.22 20.90 13.08
#> 140.1 158.1 24 168.2 145.3 150 106.2 171 159.1 168.3 117.1 8 99.1
#> 12.68 20.14 23.89 23.72 10.07 20.33 16.67 16.57 10.55 23.72 17.46 18.43 21.19
#> 57.3 100 71 34 98 46 34.1 9 34.2 71.1 163 147 11
#> 14.46 16.07 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 47 116 9.1 109 147.1 109.1 75 34.3 112 143 121 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65 94 21 144 33 142 46.1 103 135 109.2 87 142.1 165.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 31 146 21.1 11.1 72 65.1 198 84 11.2 35 33.1 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19.1 53 80 151 75.1 31.1 7 191 104 47.1 182 67 144.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19.2 87.1 103.1 163.1 20 103.2 31.2 151.1 12.1 7.1 74 163.2 53.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 120 173 74.1 185 146.1 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[67]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.015362351 0.204161755 -0.003009259
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.466828022 0.008526521 -0.090184781
#> grade_iii, Cure model
#> 0.844422551
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 188 16.16 1 46 0 1
#> 164 23.60 1 76 0 1
#> 155 13.08 1 26 0 0
#> 166 19.98 1 48 0 0
#> 4 17.64 1 NA 0 1
#> 164.1 23.60 1 76 0 1
#> 14 12.89 1 21 0 0
#> 90 20.94 1 50 0 1
#> 129 23.41 1 53 1 0
#> 150 20.33 1 48 0 0
#> 157 15.10 1 47 0 0
#> 45 17.42 1 54 0 1
#> 177 12.53 1 75 0 0
#> 57 14.46 1 45 0 1
#> 194 22.40 1 38 0 1
#> 130 16.47 1 53 0 1
#> 195 11.76 1 NA 1 0
#> 117 17.46 1 26 0 1
#> 189 10.51 1 NA 1 0
#> 92 22.92 1 47 0 1
#> 70 7.38 1 30 1 0
#> 168 23.72 1 70 0 0
#> 169 22.41 1 46 0 0
#> 8 18.43 1 32 0 0
#> 49 12.19 1 48 1 0
#> 177.1 12.53 1 75 0 0
#> 92.1 22.92 1 47 0 1
#> 66 22.13 1 53 0 0
#> 155.1 13.08 1 26 0 0
#> 133 14.65 1 57 0 0
#> 86 23.81 1 58 0 1
#> 166.1 19.98 1 48 0 0
#> 197 21.60 1 69 1 0
#> 59 10.16 1 NA 1 0
#> 55 19.34 1 69 0 1
#> 170 19.54 1 43 0 1
#> 123 13.00 1 44 1 0
#> 159 10.55 1 50 0 1
#> 183 9.24 1 67 1 0
#> 66.1 22.13 1 53 0 0
#> 153 21.33 1 55 1 0
#> 51 18.23 1 83 0 1
#> 59.1 10.16 1 NA 1 0
#> 36 21.19 1 48 0 1
#> 108 18.29 1 39 0 1
#> 91 5.33 1 61 0 1
#> 60 13.15 1 38 1 0
#> 86.1 23.81 1 58 0 1
#> 154 12.63 1 20 1 0
#> 5 16.43 1 51 0 1
#> 26 15.77 1 49 0 1
#> 30 17.43 1 78 0 0
#> 63 22.77 1 31 1 0
#> 177.2 12.53 1 75 0 0
#> 181 16.46 1 45 0 1
#> 106 16.67 1 49 1 0
#> 101 9.97 1 10 0 1
#> 36.1 21.19 1 48 0 1
#> 32 20.90 1 37 1 0
#> 96 14.54 1 33 0 1
#> 129.1 23.41 1 53 1 0
#> 76 19.22 1 54 0 1
#> 52 10.42 1 52 0 1
#> 188.1 16.16 1 46 0 1
#> 61 10.12 1 36 0 1
#> 155.2 13.08 1 26 0 0
#> 124 9.73 1 NA 1 0
#> 58 19.34 1 39 0 0
#> 66.2 22.13 1 53 0 0
#> 86.2 23.81 1 58 0 1
#> 100 16.07 1 60 0 0
#> 136 21.83 1 43 0 1
#> 195.1 11.76 1 NA 1 0
#> 175 21.91 1 43 0 0
#> 40 18.00 1 28 1 0
#> 97 19.14 1 65 0 1
#> 55.1 19.34 1 69 0 1
#> 108.1 18.29 1 39 0 1
#> 66.3 22.13 1 53 0 0
#> 100.1 16.07 1 60 0 0
#> 199 19.81 1 NA 0 1
#> 43 12.10 1 61 0 1
#> 10 10.53 1 34 0 0
#> 150.1 20.33 1 48 0 0
#> 99 21.19 1 38 0 1
#> 8.1 18.43 1 32 0 0
#> 154.1 12.63 1 20 1 0
#> 79 16.23 1 54 1 0
#> 15 22.68 1 48 0 0
#> 68 20.62 1 44 0 0
#> 194.1 22.40 1 38 0 1
#> 199.1 19.81 1 NA 0 1
#> 149 8.37 1 33 1 0
#> 40.1 18.00 1 28 1 0
#> 97.1 19.14 1 65 0 1
#> 91.1 5.33 1 61 0 1
#> 145 10.07 1 65 1 0
#> 101.1 9.97 1 10 0 1
#> 58.1 19.34 1 39 0 0
#> 127 3.53 1 62 0 1
#> 78 23.88 1 43 0 0
#> 100.2 16.07 1 60 0 0
#> 145.1 10.07 1 65 1 0
#> 100.3 16.07 1 60 0 0
#> 129.2 23.41 1 53 1 0
#> 145.2 10.07 1 65 1 0
#> 133.1 14.65 1 57 0 0
#> 192 16.44 1 31 1 0
#> 76.1 19.22 1 54 0 1
#> 108.2 18.29 1 39 0 1
#> 194.2 22.40 1 38 0 1
#> 42 12.43 1 49 0 1
#> 17 24.00 0 38 0 1
#> 44 24.00 0 56 0 0
#> 73 24.00 0 NA 0 1
#> 191 24.00 0 60 0 1
#> 160 24.00 0 31 1 0
#> 200 24.00 0 64 0 0
#> 3 24.00 0 31 1 0
#> 2 24.00 0 9 0 0
#> 142 24.00 0 53 0 0
#> 3.1 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 191.1 24.00 0 60 0 1
#> 44.1 24.00 0 56 0 0
#> 72 24.00 0 40 0 1
#> 200.1 24.00 0 64 0 0
#> 62 24.00 0 71 0 0
#> 138 24.00 0 44 1 0
#> 17.1 24.00 0 38 0 1
#> 156.1 24.00 0 50 1 0
#> 148 24.00 0 61 1 0
#> 35 24.00 0 51 0 0
#> 65 24.00 0 57 1 0
#> 17.2 24.00 0 38 0 1
#> 161 24.00 0 45 0 0
#> 27 24.00 0 63 1 0
#> 7 24.00 0 37 1 0
#> 62.1 24.00 0 71 0 0
#> 83 24.00 0 6 0 0
#> 185 24.00 0 44 1 0
#> 46 24.00 0 71 0 0
#> 47 24.00 0 38 0 1
#> 172 24.00 0 41 0 0
#> 48 24.00 0 31 1 0
#> 7.1 24.00 0 37 1 0
#> 176 24.00 0 43 0 1
#> 47.1 24.00 0 38 0 1
#> 182 24.00 0 35 0 0
#> 119 24.00 0 17 0 0
#> 94 24.00 0 51 0 1
#> 11 24.00 0 42 0 1
#> 46.1 24.00 0 71 0 0
#> 64 24.00 0 43 0 0
#> 138.1 24.00 0 44 1 0
#> 152 24.00 0 36 0 1
#> 65.1 24.00 0 57 1 0
#> 178 24.00 0 52 1 0
#> 163 24.00 0 66 0 0
#> 174 24.00 0 49 1 0
#> 146 24.00 0 63 1 0
#> 67 24.00 0 25 0 0
#> 122 24.00 0 66 0 0
#> 74 24.00 0 43 0 1
#> 46.2 24.00 0 71 0 0
#> 73.1 24.00 0 NA 0 1
#> 54 24.00 0 53 1 0
#> 12 24.00 0 63 0 0
#> 193 24.00 0 45 0 1
#> 144 24.00 0 28 0 1
#> 65.2 24.00 0 57 1 0
#> 109 24.00 0 48 0 0
#> 115 24.00 0 NA 1 0
#> 137 24.00 0 45 1 0
#> 161.1 24.00 0 45 0 0
#> 148.1 24.00 0 61 1 0
#> 185.1 24.00 0 44 1 0
#> 173 24.00 0 19 0 1
#> 160.1 24.00 0 31 1 0
#> 64.1 24.00 0 43 0 0
#> 112 24.00 0 61 0 0
#> 198 24.00 0 66 0 1
#> 172.1 24.00 0 41 0 0
#> 87 24.00 0 27 0 0
#> 47.2 24.00 0 38 0 1
#> 118 24.00 0 44 1 0
#> 185.2 24.00 0 44 1 0
#> 143 24.00 0 51 0 0
#> 83.1 24.00 0 6 0 0
#> 198.1 24.00 0 66 0 1
#> 172.2 24.00 0 41 0 0
#> 102 24.00 0 49 0 0
#> 161.2 24.00 0 45 0 0
#> 19 24.00 0 57 0 1
#> 94.1 24.00 0 51 0 1
#> 147 24.00 0 76 1 0
#> 172.3 24.00 0 41 0 0
#> 115.1 24.00 0 NA 1 0
#> 87.1 24.00 0 27 0 0
#> 64.2 24.00 0 43 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.467 NA NA NA
#> 2 age, Cure model 0.00853 NA NA NA
#> 3 grade_ii, Cure model -0.0902 NA NA NA
#> 4 grade_iii, Cure model 0.844 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0154 NA NA NA
#> 2 grade_ii, Survival model 0.204 NA NA NA
#> 3 grade_iii, Survival model -0.00301 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.466828 0.008527 -0.090185 0.844423
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.3
#> Residual Deviance: 248.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.466828022 0.008526521 -0.090184781 0.844422551
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.015362351 0.204161755 -0.003009259
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.3686940014 0.0023072924 0.5391820697 0.1107396333 0.0023072924
#> [6] 0.5971219612 0.0804240518 0.0048327182 0.0981652311 0.4556856195
#> [11] 0.2900859736 0.6418092725 0.5105684659 0.0222937791 0.3116517557
#> [16] 0.2693879440 0.0096545725 0.9264438400 0.0014281775 0.0193405742
#> [21] 0.1939629325 0.7039959030 0.6418092725 0.0096545725 0.0314662818
#> [26] 0.5391820697 0.4691243186 0.0002555826 0.1107396333 0.0550660889
#> [31] 0.1311702710 0.1241066178 0.5822539034 0.7364427480 0.8904913376
#> [36] 0.0314662818 0.0598791604 0.2396477923 0.0648826254 0.2118421717
#> [41] 0.9445463012 0.5248136638 0.0002555826 0.6120928211 0.3453712968
#> [46] 0.4424476923 0.2796032359 0.0140767540 0.6418092725 0.3227319489
#> [51] 0.3007872483 0.8553858715 0.0648826254 0.0861937348 0.4965194970
#> [56] 0.0048327182 0.1604466511 0.7696555554 0.3686940014 0.7865382691
#> [61] 0.5391820697 0.1311702710 0.0314662818 0.0002555826 0.3925810502
#> [66] 0.0504834644 0.0460942153 0.2495887233 0.1767022503 0.1311702710
#> [71] 0.2118421717 0.0314662818 0.3925810502 0.7201079569 0.7529746442
#> [76] 0.0981652311 0.0648826254 0.1939629325 0.6120928211 0.3569440767
#> [81] 0.0165998034 0.0920838872 0.0222937791 0.9084211186 0.2495887233
#> [86] 0.1767022503 0.9445463012 0.8035769863 0.8553858715 0.1311702710
#> [91] 0.9812535894 0.0000368785 0.3925810502 0.8035769863 0.3925810502
#> [96] 0.0048327182 0.8035769863 0.4691243186 0.3340059192 0.1604466511
#> [101] 0.2118421717 0.0222937791 0.6880348322 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000
#>
#> $Time
#> 188 164 155 166 164.1 14 90 129 150 157 45 177 57
#> 16.16 23.60 13.08 19.98 23.60 12.89 20.94 23.41 20.33 15.10 17.42 12.53 14.46
#> 194 130 117 92 70 168 169 8 49 177.1 92.1 66 155.1
#> 22.40 16.47 17.46 22.92 7.38 23.72 22.41 18.43 12.19 12.53 22.92 22.13 13.08
#> 133 86 166.1 197 55 170 123 159 183 66.1 153 51 36
#> 14.65 23.81 19.98 21.60 19.34 19.54 13.00 10.55 9.24 22.13 21.33 18.23 21.19
#> 108 91 60 86.1 154 5 26 30 63 177.2 181 106 101
#> 18.29 5.33 13.15 23.81 12.63 16.43 15.77 17.43 22.77 12.53 16.46 16.67 9.97
#> 36.1 32 96 129.1 76 52 188.1 61 155.2 58 66.2 86.2 100
#> 21.19 20.90 14.54 23.41 19.22 10.42 16.16 10.12 13.08 19.34 22.13 23.81 16.07
#> 136 175 40 97 55.1 108.1 66.3 100.1 43 10 150.1 99 8.1
#> 21.83 21.91 18.00 19.14 19.34 18.29 22.13 16.07 12.10 10.53 20.33 21.19 18.43
#> 154.1 79 15 68 194.1 149 40.1 97.1 91.1 145 101.1 58.1 127
#> 12.63 16.23 22.68 20.62 22.40 8.37 18.00 19.14 5.33 10.07 9.97 19.34 3.53
#> 78 100.2 145.1 100.3 129.2 145.2 133.1 192 76.1 108.2 194.2 42 17
#> 23.88 16.07 10.07 16.07 23.41 10.07 14.65 16.44 19.22 18.29 22.40 12.43 24.00
#> 44 191 160 200 3 2 142 3.1 156 191.1 44.1 72 200.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 138 17.1 156.1 148 35 65 17.2 161 27 7 62.1 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 46 47 172 48 7.1 176 47.1 182 119 94 11 46.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 138.1 152 65.1 178 163 174 146 67 122 74 46.2 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 193 144 65.2 109 137 161.1 148.1 185.1 173 160.1 64.1 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 172.1 87 47.2 118 185.2 143 83.1 198.1 172.2 102 161.2 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.1 147 172.3 87.1 64.2
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[68]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.001230402 0.880179317 0.355833287
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.582634499 0.003952111 0.598101963
#> grade_iii, Cure model
#> 1.462477656
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 157 15.10 1 47 0 0
#> 140 12.68 1 59 1 0
#> 189 10.51 1 NA 1 0
#> 66 22.13 1 53 0 0
#> 76 19.22 1 54 0 1
#> 199 19.81 1 NA 0 1
#> 100 16.07 1 60 0 0
#> 88 18.37 1 47 0 0
#> 43 12.10 1 61 0 1
#> 85 16.44 1 36 0 0
#> 134 17.81 1 47 1 0
#> 133 14.65 1 57 0 0
#> 175 21.91 1 43 0 0
#> 123 13.00 1 44 1 0
#> 194 22.40 1 38 0 1
#> 108 18.29 1 39 0 1
#> 18 15.21 1 49 1 0
#> 197 21.60 1 69 1 0
#> 5 16.43 1 51 0 1
#> 169 22.41 1 46 0 0
#> 70 7.38 1 30 1 0
#> 117 17.46 1 26 0 1
#> 4 17.64 1 NA 0 1
#> 197.1 21.60 1 69 1 0
#> 197.2 21.60 1 69 1 0
#> 79 16.23 1 54 1 0
#> 184 17.77 1 38 0 0
#> 37 12.52 1 57 1 0
#> 4.1 17.64 1 NA 0 1
#> 70.1 7.38 1 30 1 0
#> 40 18.00 1 28 1 0
#> 23 16.92 1 61 0 0
#> 134.1 17.81 1 47 1 0
#> 125 15.65 1 67 1 0
#> 195 11.76 1 NA 1 0
#> 25 6.32 1 34 1 0
#> 180 14.82 1 37 0 0
#> 125.1 15.65 1 67 1 0
#> 8 18.43 1 32 0 0
#> 56 12.21 1 60 0 0
#> 187 9.92 1 39 1 0
#> 194.1 22.40 1 38 0 1
#> 192 16.44 1 31 1 0
#> 117.1 17.46 1 26 0 1
#> 134.2 17.81 1 47 1 0
#> 91 5.33 1 61 0 1
#> 41 18.02 1 40 1 0
#> 100.1 16.07 1 60 0 0
#> 177 12.53 1 75 0 0
#> 14 12.89 1 21 0 0
#> 55 19.34 1 69 0 1
#> 45 17.42 1 54 0 1
#> 89 11.44 1 NA 0 0
#> 128 20.35 1 35 0 1
#> 63 22.77 1 31 1 0
#> 76.1 19.22 1 54 0 1
#> 170 19.54 1 43 0 1
#> 150 20.33 1 48 0 0
#> 45.1 17.42 1 54 0 1
#> 45.2 17.42 1 54 0 1
#> 77 7.27 1 67 0 1
#> 155 13.08 1 26 0 0
#> 155.1 13.08 1 26 0 0
#> 68 20.62 1 44 0 0
#> 37.1 12.52 1 57 1 0
#> 5.1 16.43 1 51 0 1
#> 68.1 20.62 1 44 0 0
#> 168 23.72 1 70 0 0
#> 60 13.15 1 38 1 0
#> 24 23.89 1 38 0 0
#> 154 12.63 1 20 1 0
#> 24.1 23.89 1 38 0 0
#> 117.2 17.46 1 26 0 1
#> 68.2 20.62 1 44 0 0
#> 76.2 19.22 1 54 0 1
#> 60.1 13.15 1 38 1 0
#> 15 22.68 1 48 0 0
#> 29 15.45 1 68 1 0
#> 97 19.14 1 65 0 1
#> 149 8.37 1 33 1 0
#> 36 21.19 1 48 0 1
#> 130 16.47 1 53 0 1
#> 117.3 17.46 1 26 0 1
#> 59 10.16 1 NA 1 0
#> 166 19.98 1 48 0 0
#> 45.3 17.42 1 54 0 1
#> 169.1 22.41 1 46 0 0
#> 108.1 18.29 1 39 0 1
#> 60.2 13.15 1 38 1 0
#> 69 23.23 1 25 0 1
#> 29.1 15.45 1 68 1 0
#> 77.1 7.27 1 67 0 1
#> 86 23.81 1 58 0 1
#> 127 3.53 1 62 0 1
#> 51 18.23 1 83 0 1
#> 78 23.88 1 43 0 0
#> 76.3 19.22 1 54 0 1
#> 59.1 10.16 1 NA 1 0
#> 86.1 23.81 1 58 0 1
#> 140.1 12.68 1 59 1 0
#> 195.1 11.76 1 NA 1 0
#> 51.1 18.23 1 83 0 1
#> 129 23.41 1 53 1 0
#> 92 22.92 1 47 0 1
#> 166.1 19.98 1 48 0 0
#> 52 10.42 1 52 0 1
#> 117.4 17.46 1 26 0 1
#> 106 16.67 1 49 1 0
#> 91.1 5.33 1 61 0 1
#> 66.1 22.13 1 53 0 0
#> 149.1 8.37 1 33 1 0
#> 124 9.73 1 NA 1 0
#> 22 24.00 0 52 1 0
#> 173 24.00 0 19 0 1
#> 104 24.00 0 50 1 0
#> 122 24.00 0 66 0 0
#> 142 24.00 0 53 0 0
#> 11 24.00 0 42 0 1
#> 121 24.00 0 57 1 0
#> 65 24.00 0 57 1 0
#> 44 24.00 0 56 0 0
#> 44.1 24.00 0 56 0 0
#> 112 24.00 0 61 0 0
#> 147 24.00 0 76 1 0
#> 62 24.00 0 71 0 0
#> 131 24.00 0 66 0 0
#> 131.1 24.00 0 66 0 0
#> 186 24.00 0 45 1 0
#> 172 24.00 0 41 0 0
#> 142.1 24.00 0 53 0 0
#> 48 24.00 0 31 1 0
#> 131.2 24.00 0 66 0 0
#> 87 24.00 0 27 0 0
#> 74 24.00 0 43 0 1
#> 75 24.00 0 21 1 0
#> 64 24.00 0 43 0 0
#> 98 24.00 0 34 1 0
#> 131.3 24.00 0 66 0 0
#> 33 24.00 0 53 0 0
#> 200 24.00 0 64 0 0
#> 20 24.00 0 46 1 0
#> 64.1 24.00 0 43 0 0
#> 54 24.00 0 53 1 0
#> 82 24.00 0 34 0 0
#> 198 24.00 0 66 0 1
#> 94 24.00 0 51 0 1
#> 151 24.00 0 42 0 0
#> 95 24.00 0 68 0 1
#> 132 24.00 0 55 0 0
#> 173.1 24.00 0 19 0 1
#> 141 24.00 0 44 1 0
#> 109 24.00 0 48 0 0
#> 186.1 24.00 0 45 1 0
#> 165 24.00 0 47 0 0
#> 31 24.00 0 36 0 1
#> 102 24.00 0 49 0 0
#> 27 24.00 0 63 1 0
#> 163 24.00 0 66 0 0
#> 143 24.00 0 51 0 0
#> 191 24.00 0 60 0 1
#> 121.1 24.00 0 57 1 0
#> 35 24.00 0 51 0 0
#> 83 24.00 0 6 0 0
#> 165.1 24.00 0 47 0 0
#> 9 24.00 0 31 1 0
#> 74.1 24.00 0 43 0 1
#> 200.1 24.00 0 64 0 0
#> 162 24.00 0 51 0 0
#> 178 24.00 0 52 1 0
#> 115 24.00 0 NA 1 0
#> 2 24.00 0 9 0 0
#> 148 24.00 0 61 1 0
#> 74.2 24.00 0 43 0 1
#> 165.2 24.00 0 47 0 0
#> 64.2 24.00 0 43 0 0
#> 98.1 24.00 0 34 1 0
#> 126 24.00 0 48 0 0
#> 102.1 24.00 0 49 0 0
#> 73 24.00 0 NA 0 1
#> 141.1 24.00 0 44 1 0
#> 161 24.00 0 45 0 0
#> 11.1 24.00 0 42 0 1
#> 1 24.00 0 23 1 0
#> 200.2 24.00 0 64 0 0
#> 126.1 24.00 0 48 0 0
#> 20.1 24.00 0 46 1 0
#> 98.2 24.00 0 34 1 0
#> 28 24.00 0 67 1 0
#> 165.3 24.00 0 47 0 0
#> 94.1 24.00 0 51 0 1
#> 3 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 64.3 24.00 0 43 0 0
#> 137 24.00 0 45 1 0
#> 82.1 24.00 0 34 0 0
#> 109.1 24.00 0 48 0 0
#> 119 24.00 0 17 0 0
#> 54.1 24.00 0 53 1 0
#> 182 24.00 0 35 0 0
#> 82.2 24.00 0 34 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.583 NA NA NA
#> 2 age, Cure model 0.00395 NA NA NA
#> 3 grade_ii, Cure model 0.598 NA NA NA
#> 4 grade_iii, Cure model 1.46 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00123 NA NA NA
#> 2 grade_ii, Survival model 0.880 NA NA NA
#> 3 grade_iii, Survival model 0.356 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.582634 0.003952 0.598102 1.462478
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.3
#> Residual Deviance: 244.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.582634499 0.003952111 0.598101963 1.462477656
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.001230402 0.880179317 0.355833287
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.79212615 0.86569261 0.25345591 0.43085528 0.73761359 0.49124634
#> [7] 0.91447950 0.69695069 0.56061016 0.80728368 0.27856223 0.85120901
#> [13] 0.22850750 0.50150561 0.78455306 0.29144247 0.71331901 0.20253616
#> [19] 0.94828451 0.59598596 0.29144247 0.29144247 0.72956042 0.58703565
#> [25] 0.89386562 0.94828451 0.55107706 0.67167150 0.56061016 0.75365681
#> [31] 0.97430880 0.79970332 0.75365681 0.48099910 0.90758830 0.92821097
#> [37] 0.22850750 0.69695069 0.59598596 0.56061016 0.98076614 0.54131951
#> [43] 0.73761359 0.88684266 0.85845003 0.42016891 0.63823783 0.36626641
#> [49] 0.17592755 0.43085528 0.40939730 0.37709449 0.63823783 0.63823783
#> [55] 0.96132434 0.83662998 0.83662998 0.33439748 0.89386562 0.71331901
#> [61] 0.33439748 0.11136103 0.81486887 0.01914948 0.87982461 0.01914948
#> [67] 0.59598596 0.33439748 0.43085528 0.81486887 0.18920485 0.76929378
#> [73] 0.47076029 0.93500289 0.32347546 0.68859175 0.59598596 0.38794046
#> [79] 0.63823783 0.20253616 0.50150561 0.81486887 0.14595291 0.76929378
#> [85] 0.96132434 0.07748969 0.99358377 0.52152222 0.05460584 0.43085528
#> [91] 0.07748969 0.86569261 0.52152222 0.13009086 0.16118139 0.38794046
#> [97] 0.92135390 0.59598596 0.68019845 0.98076614 0.25345591 0.93500289
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 157 140 66 76 100 88 43 85 134 133 175 123 194
#> 15.10 12.68 22.13 19.22 16.07 18.37 12.10 16.44 17.81 14.65 21.91 13.00 22.40
#> 108 18 197 5 169 70 117 197.1 197.2 79 184 37 70.1
#> 18.29 15.21 21.60 16.43 22.41 7.38 17.46 21.60 21.60 16.23 17.77 12.52 7.38
#> 40 23 134.1 125 25 180 125.1 8 56 187 194.1 192 117.1
#> 18.00 16.92 17.81 15.65 6.32 14.82 15.65 18.43 12.21 9.92 22.40 16.44 17.46
#> 134.2 91 41 100.1 177 14 55 45 128 63 76.1 170 150
#> 17.81 5.33 18.02 16.07 12.53 12.89 19.34 17.42 20.35 22.77 19.22 19.54 20.33
#> 45.1 45.2 77 155 155.1 68 37.1 5.1 68.1 168 60 24 154
#> 17.42 17.42 7.27 13.08 13.08 20.62 12.52 16.43 20.62 23.72 13.15 23.89 12.63
#> 24.1 117.2 68.2 76.2 60.1 15 29 97 149 36 130 117.3 166
#> 23.89 17.46 20.62 19.22 13.15 22.68 15.45 19.14 8.37 21.19 16.47 17.46 19.98
#> 45.3 169.1 108.1 60.2 69 29.1 77.1 86 127 51 78 76.3 86.1
#> 17.42 22.41 18.29 13.15 23.23 15.45 7.27 23.81 3.53 18.23 23.88 19.22 23.81
#> 140.1 51.1 129 92 166.1 52 117.4 106 91.1 66.1 149.1 22 173
#> 12.68 18.23 23.41 22.92 19.98 10.42 17.46 16.67 5.33 22.13 8.37 24.00 24.00
#> 104 122 142 11 121 65 44 44.1 112 147 62 131 131.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 172 142.1 48 131.2 87 74 75 64 98 131.3 33 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 64.1 54 82 198 94 151 95 132 173.1 141 109 186.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 31 102 27 163 143 191 121.1 35 83 165.1 9 74.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200.1 162 178 2 148 74.2 165.2 64.2 98.1 126 102.1 141.1 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11.1 1 200.2 126.1 20.1 98.2 28 165.3 94.1 3 21 64.3 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82.1 109.1 119 54.1 182 82.2
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[69]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.008208474 0.843390729 0.378341683
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.46572932 0.01006809 -0.04017733
#> grade_iii, Cure model
#> 0.52358553
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 51 18.23 1 83 0 1
#> 130 16.47 1 53 0 1
#> 130.1 16.47 1 53 0 1
#> 4 17.64 1 NA 0 1
#> 45 17.42 1 54 0 1
#> 106 16.67 1 49 1 0
#> 32 20.90 1 37 1 0
#> 145 10.07 1 65 1 0
#> 184 17.77 1 38 0 0
#> 93 10.33 1 52 0 1
#> 92 22.92 1 47 0 1
#> 81 14.06 1 34 0 0
#> 187 9.92 1 39 1 0
#> 177 12.53 1 75 0 0
#> 55 19.34 1 69 0 1
#> 57 14.46 1 45 0 1
#> 183 9.24 1 67 1 0
#> 68 20.62 1 44 0 0
#> 153 21.33 1 55 1 0
#> 90 20.94 1 50 0 1
#> 117 17.46 1 26 0 1
#> 100 16.07 1 60 0 0
#> 139 21.49 1 63 1 0
#> 155 13.08 1 26 0 0
#> 136 21.83 1 43 0 1
#> 145.1 10.07 1 65 1 0
#> 85 16.44 1 36 0 0
#> 124 9.73 1 NA 1 0
#> 106.1 16.67 1 49 1 0
#> 113 22.86 1 34 0 0
#> 110 17.56 1 65 0 1
#> 134 17.81 1 47 1 0
#> 101 9.97 1 10 0 1
#> 85.1 16.44 1 36 0 0
#> 133 14.65 1 57 0 0
#> 124.1 9.73 1 NA 1 0
#> 100.1 16.07 1 60 0 0
#> 179 18.63 1 42 0 0
#> 175 21.91 1 43 0 0
#> 78 23.88 1 43 0 0
#> 26 15.77 1 49 0 1
#> 136.1 21.83 1 43 0 1
#> 199 19.81 1 NA 0 1
#> 171 16.57 1 41 0 1
#> 68.1 20.62 1 44 0 0
#> 187.1 9.92 1 39 1 0
#> 96 14.54 1 33 0 1
#> 149 8.37 1 33 1 0
#> 113.1 22.86 1 34 0 0
#> 36 21.19 1 48 0 1
#> 199.1 19.81 1 NA 0 1
#> 89 11.44 1 NA 0 0
#> 171.1 16.57 1 41 0 1
#> 45.1 17.42 1 54 0 1
#> 89.1 11.44 1 NA 0 0
#> 91 5.33 1 61 0 1
#> 169 22.41 1 46 0 0
#> 189 10.51 1 NA 1 0
#> 93.1 10.33 1 52 0 1
#> 90.1 20.94 1 50 0 1
#> 92.1 22.92 1 47 0 1
#> 110.1 17.56 1 65 0 1
#> 23 16.92 1 61 0 0
#> 99 21.19 1 38 0 1
#> 60 13.15 1 38 1 0
#> 66 22.13 1 53 0 0
#> 139.1 21.49 1 63 1 0
#> 90.2 20.94 1 50 0 1
#> 128 20.35 1 35 0 1
#> 16 8.71 1 71 0 1
#> 187.2 9.92 1 39 1 0
#> 40 18.00 1 28 1 0
#> 25 6.32 1 34 1 0
#> 76 19.22 1 54 0 1
#> 42 12.43 1 49 0 1
#> 96.1 14.54 1 33 0 1
#> 154 12.63 1 20 1 0
#> 36.1 21.19 1 48 0 1
#> 56 12.21 1 60 0 0
#> 167 15.55 1 56 1 0
#> 55.1 19.34 1 69 0 1
#> 32.1 20.90 1 37 1 0
#> 14 12.89 1 21 0 0
#> 168 23.72 1 70 0 0
#> 60.1 13.15 1 38 1 0
#> 66.1 22.13 1 53 0 0
#> 187.3 9.92 1 39 1 0
#> 29 15.45 1 68 1 0
#> 18 15.21 1 49 1 0
#> 77 7.27 1 67 0 1
#> 99.1 21.19 1 38 0 1
#> 89.2 11.44 1 NA 0 0
#> 111 17.45 1 47 0 1
#> 107 11.18 1 54 1 0
#> 89.3 11.44 1 NA 0 0
#> 190 20.81 1 42 1 0
#> 117.1 17.46 1 26 0 1
#> 168.1 23.72 1 70 0 0
#> 136.2 21.83 1 43 0 1
#> 25.1 6.32 1 34 1 0
#> 88 18.37 1 47 0 0
#> 37 12.52 1 57 1 0
#> 81.1 14.06 1 34 0 0
#> 61 10.12 1 36 0 1
#> 51.1 18.23 1 83 0 1
#> 100.2 16.07 1 60 0 0
#> 190.1 20.81 1 42 1 0
#> 153.1 21.33 1 55 1 0
#> 10 10.53 1 34 0 0
#> 114 13.68 1 NA 0 0
#> 166 19.98 1 48 0 0
#> 23.1 16.92 1 61 0 0
#> 33 24.00 0 53 0 0
#> 120 24.00 0 68 0 1
#> 200 24.00 0 64 0 0
#> 62 24.00 0 71 0 0
#> 144 24.00 0 28 0 1
#> 98 24.00 0 34 1 0
#> 186 24.00 0 45 1 0
#> 80 24.00 0 41 0 0
#> 144.1 24.00 0 28 0 1
#> 147 24.00 0 76 1 0
#> 71 24.00 0 51 0 0
#> 80.1 24.00 0 41 0 0
#> 53 24.00 0 32 0 1
#> 22 24.00 0 52 1 0
#> 196 24.00 0 19 0 0
#> 47 24.00 0 38 0 1
#> 141 24.00 0 44 1 0
#> 109 24.00 0 48 0 0
#> 176 24.00 0 43 0 1
#> 147.1 24.00 0 76 1 0
#> 178 24.00 0 52 1 0
#> 71.1 24.00 0 51 0 0
#> 120.1 24.00 0 68 0 1
#> 186.1 24.00 0 45 1 0
#> 11 24.00 0 42 0 1
#> 83 24.00 0 6 0 0
#> 116 24.00 0 58 0 1
#> 193 24.00 0 45 0 1
#> 172 24.00 0 41 0 0
#> 27 24.00 0 63 1 0
#> 46 24.00 0 71 0 0
#> 142 24.00 0 53 0 0
#> 116.1 24.00 0 58 0 1
#> 116.2 24.00 0 58 0 1
#> 34 24.00 0 36 0 0
#> 172.1 24.00 0 41 0 0
#> 186.2 24.00 0 45 1 0
#> 48 24.00 0 31 1 0
#> 103 24.00 0 56 1 0
#> 198 24.00 0 66 0 1
#> 20 24.00 0 46 1 0
#> 119 24.00 0 17 0 0
#> 75 24.00 0 21 1 0
#> 64 24.00 0 43 0 0
#> 38 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 138 24.00 0 44 1 0
#> 3 24.00 0 31 1 0
#> 34.1 24.00 0 36 0 0
#> 109.1 24.00 0 48 0 0
#> 65 24.00 0 57 1 0
#> 104 24.00 0 50 1 0
#> 126 24.00 0 48 0 0
#> 103.1 24.00 0 56 1 0
#> 9 24.00 0 31 1 0
#> 9.1 24.00 0 31 1 0
#> 144.2 24.00 0 28 0 1
#> 115 24.00 0 NA 1 0
#> 162 24.00 0 51 0 0
#> 98.1 24.00 0 34 1 0
#> 62.1 24.00 0 71 0 0
#> 185 24.00 0 44 1 0
#> 162.1 24.00 0 51 0 0
#> 47.1 24.00 0 38 0 1
#> 118.1 24.00 0 44 1 0
#> 116.3 24.00 0 58 0 1
#> 44 24.00 0 56 0 0
#> 64.1 24.00 0 43 0 0
#> 74 24.00 0 43 0 1
#> 147.2 24.00 0 76 1 0
#> 47.2 24.00 0 38 0 1
#> 118.2 24.00 0 44 1 0
#> 27.1 24.00 0 63 1 0
#> 62.2 24.00 0 71 0 0
#> 196.1 24.00 0 19 0 0
#> 53.1 24.00 0 32 0 1
#> 109.2 24.00 0 48 0 0
#> 173 24.00 0 19 0 1
#> 73 24.00 0 NA 0 1
#> 54 24.00 0 53 1 0
#> 120.2 24.00 0 68 0 1
#> 20.1 24.00 0 46 1 0
#> 119.1 24.00 0 17 0 0
#> 73.1 24.00 0 NA 0 1
#> 161 24.00 0 45 0 0
#> 176.1 24.00 0 43 0 1
#> 176.2 24.00 0 43 0 1
#> 84 24.00 0 39 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.466 NA NA NA
#> 2 age, Cure model 0.0101 NA NA NA
#> 3 grade_ii, Cure model -0.0402 NA NA NA
#> 4 grade_iii, Cure model 0.524 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00821 NA NA NA
#> 2 grade_ii, Survival model 0.843 NA NA NA
#> 3 grade_iii, Survival model 0.378 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.46573 0.01007 -0.04018 0.52359
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.5
#> Residual Deviance: 252.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.46572932 0.01006809 -0.04017733 0.52358553
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.008208474 0.843390729 0.378341683
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.385409856 0.563450104 0.563450104 0.484700316 0.524349913 0.258612659
#> [7] 0.869391126 0.425475670 0.840159658 0.025522987 0.712588173 0.898331591
#> [13] 0.781510392 0.335857905 0.702633511 0.935270226 0.297127000 0.167224865
#> [19] 0.228020223 0.455174496 0.602764945 0.144751172 0.752025470 0.110433176
#> [25] 0.869391126 0.583022719 0.524349913 0.043121283 0.435408037 0.415605055
#> [31] 0.888673737 0.583022719 0.672871685 0.602764945 0.365317956 0.097470836
#> [37] 0.002059552 0.632701933 0.110433176 0.543914964 0.297127000 0.898331591
#> [43] 0.682862724 0.953972818 0.043121283 0.188342775 0.543914964 0.484700316
#> [49] 0.990820464 0.062771029 0.840159658 0.228020223 0.025522987 0.435408037
#> [55] 0.504371622 0.188342775 0.732492946 0.074130399 0.144751172 0.228020223
#> [61] 0.316323120 0.944612963 0.898331591 0.405596527 0.972565826 0.355394295
#> [67] 0.801076143 0.682862724 0.771756249 0.188342775 0.810834266 0.642846429
#> [73] 0.335857905 0.258612659 0.761880745 0.008548610 0.732492946 0.074130399
#> [79] 0.898331591 0.652916602 0.662935777 0.963262247 0.188342775 0.474788392
#> [85] 0.820638277 0.278299893 0.455174496 0.008548610 0.110433176 0.972565826
#> [91] 0.375320866 0.791320825 0.712588173 0.859616587 0.385409856 0.602764945
#> [97] 0.278299893 0.167224865 0.830384997 0.326042862 0.504371622 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 51 130 130.1 45 106 32 145 184 93 92 81 187 177
#> 18.23 16.47 16.47 17.42 16.67 20.90 10.07 17.77 10.33 22.92 14.06 9.92 12.53
#> 55 57 183 68 153 90 117 100 139 155 136 145.1 85
#> 19.34 14.46 9.24 20.62 21.33 20.94 17.46 16.07 21.49 13.08 21.83 10.07 16.44
#> 106.1 113 110 134 101 85.1 133 100.1 179 175 78 26 136.1
#> 16.67 22.86 17.56 17.81 9.97 16.44 14.65 16.07 18.63 21.91 23.88 15.77 21.83
#> 171 68.1 187.1 96 149 113.1 36 171.1 45.1 91 169 93.1 90.1
#> 16.57 20.62 9.92 14.54 8.37 22.86 21.19 16.57 17.42 5.33 22.41 10.33 20.94
#> 92.1 110.1 23 99 60 66 139.1 90.2 128 16 187.2 40 25
#> 22.92 17.56 16.92 21.19 13.15 22.13 21.49 20.94 20.35 8.71 9.92 18.00 6.32
#> 76 42 96.1 154 36.1 56 167 55.1 32.1 14 168 60.1 66.1
#> 19.22 12.43 14.54 12.63 21.19 12.21 15.55 19.34 20.90 12.89 23.72 13.15 22.13
#> 187.3 29 18 77 99.1 111 107 190 117.1 168.1 136.2 25.1 88
#> 9.92 15.45 15.21 7.27 21.19 17.45 11.18 20.81 17.46 23.72 21.83 6.32 18.37
#> 37 81.1 61 51.1 100.2 190.1 153.1 10 166 23.1 33 120 200
#> 12.52 14.06 10.12 18.23 16.07 20.81 21.33 10.53 19.98 16.92 24.00 24.00 24.00
#> 62 144 98 186 80 144.1 147 71 80.1 53 22 196 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 109 176 147.1 178 71.1 120.1 186.1 11 83 116 193 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 46 142 116.1 116.2 34 172.1 186.2 48 103 198 20 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 64 38 118 138 3 34.1 109.1 65 104 126 103.1 9
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.1 144.2 162 98.1 62.1 185 162.1 47.1 118.1 116.3 44 64.1 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147.2 47.2 118.2 27.1 62.2 196.1 53.1 109.2 173 54 120.2 20.1 119.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 176.1 176.2 84
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[70]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01090299 1.18826882 0.65321961
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.596569983 0.007526452 0.240747575
#> grade_iii, Cure model
#> 1.039132115
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 89 11.44 1 NA 0 0
#> 29 15.45 1 68 1 0
#> 149 8.37 1 33 1 0
#> 100 16.07 1 60 0 0
#> 188 16.16 1 46 0 1
#> 37 12.52 1 57 1 0
#> 111 17.45 1 47 0 1
#> 188.1 16.16 1 46 0 1
#> 127 3.53 1 62 0 1
#> 154 12.63 1 20 1 0
#> 25 6.32 1 34 1 0
#> 85 16.44 1 36 0 0
#> 150 20.33 1 48 0 0
#> 51 18.23 1 83 0 1
#> 66 22.13 1 53 0 0
#> 4 17.64 1 NA 0 1
#> 78 23.88 1 43 0 0
#> 145 10.07 1 65 1 0
#> 88 18.37 1 47 0 0
#> 117 17.46 1 26 0 1
#> 134 17.81 1 47 1 0
#> 61 10.12 1 36 0 1
#> 183 9.24 1 67 1 0
#> 39 15.59 1 37 0 1
#> 91 5.33 1 61 0 1
#> 93 10.33 1 52 0 1
#> 188.2 16.16 1 46 0 1
#> 10 10.53 1 34 0 0
#> 85.1 16.44 1 36 0 0
#> 85.2 16.44 1 36 0 0
#> 197 21.60 1 69 1 0
#> 195 11.76 1 NA 1 0
#> 25.1 6.32 1 34 1 0
#> 4.1 17.64 1 NA 0 1
#> 110 17.56 1 65 0 1
#> 10.1 10.53 1 34 0 0
#> 18 15.21 1 49 1 0
#> 36 21.19 1 48 0 1
#> 90 20.94 1 50 0 1
#> 150.1 20.33 1 48 0 0
#> 68 20.62 1 44 0 0
#> 69 23.23 1 25 0 1
#> 170 19.54 1 43 0 1
#> 93.1 10.33 1 52 0 1
#> 106 16.67 1 49 1 0
#> 13 14.34 1 54 0 1
#> 117.1 17.46 1 26 0 1
#> 76 19.22 1 54 0 1
#> 139 21.49 1 63 1 0
#> 113 22.86 1 34 0 0
#> 23 16.92 1 61 0 0
#> 96 14.54 1 33 0 1
#> 97 19.14 1 65 0 1
#> 24 23.89 1 38 0 0
#> 179 18.63 1 42 0 0
#> 194 22.40 1 38 0 1
#> 164 23.60 1 76 0 1
#> 100.1 16.07 1 60 0 0
#> 164.1 23.60 1 76 0 1
#> 155 13.08 1 26 0 0
#> 155.1 13.08 1 26 0 0
#> 113.1 22.86 1 34 0 0
#> 60 13.15 1 38 1 0
#> 168 23.72 1 70 0 0
#> 188.3 16.16 1 46 0 1
#> 171 16.57 1 41 0 1
#> 164.2 23.60 1 76 0 1
#> 57 14.46 1 45 0 1
#> 43 12.10 1 61 0 1
#> 127.1 3.53 1 62 0 1
#> 15 22.68 1 48 0 0
#> 194.1 22.40 1 38 0 1
#> 145.1 10.07 1 65 1 0
#> 183.1 9.24 1 67 1 0
#> 55 19.34 1 69 0 1
#> 113.2 22.86 1 34 0 0
#> 89.1 11.44 1 NA 0 0
#> 32 20.90 1 37 1 0
#> 124 9.73 1 NA 1 0
#> 180 14.82 1 37 0 0
#> 76.1 19.22 1 54 0 1
#> 43.1 12.10 1 61 0 1
#> 70 7.38 1 30 1 0
#> 183.2 9.24 1 67 1 0
#> 26 15.77 1 49 0 1
#> 145.2 10.07 1 65 1 0
#> 179.1 18.63 1 42 0 0
#> 5 16.43 1 51 0 1
#> 29.1 15.45 1 68 1 0
#> 187 9.92 1 39 1 0
#> 164.3 23.60 1 76 0 1
#> 68.1 20.62 1 44 0 0
#> 91.1 5.33 1 61 0 1
#> 101 9.97 1 10 0 1
#> 10.2 10.53 1 34 0 0
#> 108 18.29 1 39 0 1
#> 88.1 18.37 1 47 0 0
#> 51.1 18.23 1 83 0 1
#> 24.1 23.89 1 38 0 0
#> 14 12.89 1 21 0 0
#> 41 18.02 1 40 1 0
#> 42 12.43 1 49 0 1
#> 108.1 18.29 1 39 0 1
#> 99 21.19 1 38 0 1
#> 159 10.55 1 50 0 1
#> 63 22.77 1 31 1 0
#> 123 13.00 1 44 1 0
#> 89.2 11.44 1 NA 0 0
#> 158 20.14 1 74 1 0
#> 78.1 23.88 1 43 0 0
#> 70.1 7.38 1 30 1 0
#> 42.1 12.43 1 49 0 1
#> 198 24.00 0 66 0 1
#> 54 24.00 0 53 1 0
#> 31 24.00 0 36 0 1
#> 34 24.00 0 36 0 0
#> 9 24.00 0 31 1 0
#> 62 24.00 0 71 0 0
#> 46 24.00 0 71 0 0
#> 152 24.00 0 36 0 1
#> 31.1 24.00 0 36 0 1
#> 132 24.00 0 55 0 0
#> 185 24.00 0 44 1 0
#> 2 24.00 0 9 0 0
#> 156 24.00 0 50 1 0
#> 84 24.00 0 39 0 1
#> 165 24.00 0 47 0 0
#> 143 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 200 24.00 0 64 0 0
#> 75 24.00 0 21 1 0
#> 135 24.00 0 58 1 0
#> 71 24.00 0 51 0 0
#> 131 24.00 0 66 0 0
#> 151 24.00 0 42 0 0
#> 21 24.00 0 47 0 0
#> 20 24.00 0 46 1 0
#> 75.1 24.00 0 21 1 0
#> 156.1 24.00 0 50 1 0
#> 174 24.00 0 49 1 0
#> 87 24.00 0 27 0 0
#> 148 24.00 0 61 1 0
#> 84.1 24.00 0 39 0 1
#> 11 24.00 0 42 0 1
#> 7 24.00 0 37 1 0
#> 172 24.00 0 41 0 0
#> 80 24.00 0 41 0 0
#> 152.1 24.00 0 36 0 1
#> 163 24.00 0 66 0 0
#> 161 24.00 0 45 0 0
#> 200.1 24.00 0 64 0 0
#> 82 24.00 0 34 0 0
#> 87.1 24.00 0 27 0 0
#> 62.1 24.00 0 71 0 0
#> 151.1 24.00 0 42 0 0
#> 12 24.00 0 63 0 0
#> 172.1 24.00 0 41 0 0
#> 144 24.00 0 28 0 1
#> 122 24.00 0 66 0 0
#> 82.1 24.00 0 34 0 0
#> 1 24.00 0 23 1 0
#> 17 24.00 0 38 0 1
#> 138 24.00 0 44 1 0
#> 28 24.00 0 67 1 0
#> 118 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 19 24.00 0 57 0 1
#> 2.1 24.00 0 9 0 0
#> 48 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 120 24.00 0 68 0 1
#> 64 24.00 0 43 0 0
#> 173 24.00 0 19 0 1
#> 21.1 24.00 0 47 0 0
#> 132.1 24.00 0 55 0 0
#> 20.1 24.00 0 46 1 0
#> 62.2 24.00 0 71 0 0
#> 146 24.00 0 63 1 0
#> 116 24.00 0 58 0 1
#> 138.1 24.00 0 44 1 0
#> 98 24.00 0 34 1 0
#> 31.2 24.00 0 36 0 1
#> 198.1 24.00 0 66 0 1
#> 162 24.00 0 51 0 0
#> 152.2 24.00 0 36 0 1
#> 21.2 24.00 0 47 0 0
#> 173.1 24.00 0 19 0 1
#> 142 24.00 0 53 0 0
#> 7.1 24.00 0 37 1 0
#> 191 24.00 0 60 0 1
#> 2.2 24.00 0 9 0 0
#> 144.1 24.00 0 28 0 1
#> 143.1 24.00 0 51 0 0
#> 48.1 24.00 0 31 1 0
#> 132.2 24.00 0 55 0 0
#> 143.2 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 147 24.00 0 76 1 0
#> 118.1 24.00 0 44 1 0
#> 54.1 24.00 0 53 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.597 NA NA NA
#> 2 age, Cure model 0.00753 NA NA NA
#> 3 grade_ii, Cure model 0.241 NA NA NA
#> 4 grade_iii, Cure model 1.04 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0109 NA NA NA
#> 2 grade_ii, Survival model 1.19 NA NA NA
#> 3 grade_iii, Survival model 0.653 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.596570 0.007526 0.240748 1.039132
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 266.1
#> Residual Deviance: 255.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.596569983 0.007526452 0.240747575 1.039132115
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01090299 1.18826882 0.65321961
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.63109355 0.92756162 0.59222054 0.55463795 0.75225921 0.47728160
#> [7] 0.55463795 0.98406340 0.74323955 0.95220494 0.51608647 0.26575008
#> [13] 0.40728094 0.17364503 0.01498139 0.85900686 0.36620693 0.45796450
#> [19] 0.43807170 0.85006415 0.90238316 0.62137854 0.96813262 0.83221717
#> [25] 0.55463795 0.80553951 0.51608647 0.51608647 0.18487073 0.95220494
#> [31] 0.44801214 0.80553951 0.65004784 0.20622294 0.22625941 0.26575008
#> [37] 0.24615647 0.08465187 0.29606749 0.83221717 0.49683342 0.68774669
#> [43] 0.45796450 0.31619278 0.19573620 0.09613863 0.48700984 0.66893178
#> [49] 0.33594600 0.00329853 0.34598841 0.15249955 0.04529178 0.59222054
#> [55] 0.04529178 0.70637610 0.70637610 0.09613863 0.69713409 0.03259289
#> [61] 0.55463795 0.50648089 0.04529178 0.67835075 0.77891584 0.98406340
#> [67] 0.14109257 0.15249955 0.85900686 0.90238316 0.30611452 0.09613863
#> [73] 0.23645720 0.65946738 0.31619278 0.77891584 0.93593296 0.90238316
#> [79] 0.61162024 0.85900686 0.34598841 0.54488278 0.63109355 0.89377023
#> [85] 0.04529178 0.24615647 0.96813262 0.88506122 0.80553951 0.38688336
#> [91] 0.36620693 0.40728094 0.00329853 0.73403690 0.42790859 0.76119715
#> [97] 0.38688336 0.20622294 0.79663930 0.13004965 0.72485781 0.28595099
#> [103] 0.01498139 0.93593296 0.76119715 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000
#>
#> $Time
#> 29 149 100 188 37 111 188.1 127 154 25 85 150 51
#> 15.45 8.37 16.07 16.16 12.52 17.45 16.16 3.53 12.63 6.32 16.44 20.33 18.23
#> 66 78 145 88 117 134 61 183 39 91 93 188.2 10
#> 22.13 23.88 10.07 18.37 17.46 17.81 10.12 9.24 15.59 5.33 10.33 16.16 10.53
#> 85.1 85.2 197 25.1 110 10.1 18 36 90 150.1 68 69 170
#> 16.44 16.44 21.60 6.32 17.56 10.53 15.21 21.19 20.94 20.33 20.62 23.23 19.54
#> 93.1 106 13 117.1 76 139 113 23 96 97 24 179 194
#> 10.33 16.67 14.34 17.46 19.22 21.49 22.86 16.92 14.54 19.14 23.89 18.63 22.40
#> 164 100.1 164.1 155 155.1 113.1 60 168 188.3 171 164.2 57 43
#> 23.60 16.07 23.60 13.08 13.08 22.86 13.15 23.72 16.16 16.57 23.60 14.46 12.10
#> 127.1 15 194.1 145.1 183.1 55 113.2 32 180 76.1 43.1 70 183.2
#> 3.53 22.68 22.40 10.07 9.24 19.34 22.86 20.90 14.82 19.22 12.10 7.38 9.24
#> 26 145.2 179.1 5 29.1 187 164.3 68.1 91.1 101 10.2 108 88.1
#> 15.77 10.07 18.63 16.43 15.45 9.92 23.60 20.62 5.33 9.97 10.53 18.29 18.37
#> 51.1 24.1 14 41 42 108.1 99 159 63 123 158 78.1 70.1
#> 18.23 23.89 12.89 18.02 12.43 18.29 21.19 10.55 22.77 13.00 20.14 23.88 7.38
#> 42.1 198 54 31 34 9 62 46 152 31.1 132 185 2
#> 12.43 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 84 165 143 44 200 75 135 71 131 151 21 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75.1 156.1 174 87 148 84.1 11 7 172 80 152.1 163 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200.1 82 87.1 62.1 151.1 12 172.1 144 122 82.1 1 17 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 118 95 19 2.1 48 137 120 64 173 21.1 132.1 20.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62.2 146 116 138.1 98 31.2 198.1 162 152.2 21.2 173.1 142 7.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191 2.2 144.1 143.1 48.1 132.2 143.2 126 147 118.1 54.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[71]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.007239893 0.556948434 0.394114489
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.73346778 0.01528774 0.23421124
#> grade_iii, Cure model
#> 0.46183589
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 154 12.63 1 20 1 0
#> 79 16.23 1 54 1 0
#> 175 21.91 1 43 0 0
#> 194 22.40 1 38 0 1
#> 179 18.63 1 42 0 0
#> 169 22.41 1 46 0 0
#> 150 20.33 1 48 0 0
#> 100 16.07 1 60 0 0
#> 190 20.81 1 42 1 0
#> 117 17.46 1 26 0 1
#> 91 5.33 1 61 0 1
#> 187 9.92 1 39 1 0
#> 91.1 5.33 1 61 0 1
#> 108 18.29 1 39 0 1
#> 39 15.59 1 37 0 1
#> 123 13.00 1 44 1 0
#> 39.1 15.59 1 37 0 1
#> 154.1 12.63 1 20 1 0
#> 57 14.46 1 45 0 1
#> 6 15.64 1 39 0 0
#> 128 20.35 1 35 0 1
#> 100.1 16.07 1 60 0 0
#> 97 19.14 1 65 0 1
#> 50 10.02 1 NA 1 0
#> 52 10.42 1 52 0 1
#> 76 19.22 1 54 0 1
#> 133 14.65 1 57 0 0
#> 157 15.10 1 47 0 0
#> 40 18.00 1 28 1 0
#> 140 12.68 1 59 1 0
#> 123.1 13.00 1 44 1 0
#> 106 16.67 1 49 1 0
#> 8 18.43 1 32 0 0
#> 49 12.19 1 48 1 0
#> 153 21.33 1 55 1 0
#> 167 15.55 1 56 1 0
#> 14 12.89 1 21 0 0
#> 59 10.16 1 NA 1 0
#> 32 20.90 1 37 1 0
#> 169.1 22.41 1 46 0 0
#> 85 16.44 1 36 0 0
#> 23 16.92 1 61 0 0
#> 125 15.65 1 67 1 0
#> 157.1 15.10 1 47 0 0
#> 25 6.32 1 34 1 0
#> 6.1 15.64 1 39 0 0
#> 168 23.72 1 70 0 0
#> 100.2 16.07 1 60 0 0
#> 37 12.52 1 57 1 0
#> 134 17.81 1 47 1 0
#> 89 11.44 1 NA 0 0
#> 157.2 15.10 1 47 0 0
#> 18 15.21 1 49 1 0
#> 56 12.21 1 60 0 0
#> 52.1 10.42 1 52 0 1
#> 16 8.71 1 71 0 1
#> 52.2 10.42 1 52 0 1
#> 36 21.19 1 48 0 1
#> 79.1 16.23 1 54 1 0
#> 195 11.76 1 NA 1 0
#> 25.1 6.32 1 34 1 0
#> 171 16.57 1 41 0 1
#> 158 20.14 1 74 1 0
#> 187.1 9.92 1 39 1 0
#> 49.1 12.19 1 48 1 0
#> 50.1 10.02 1 NA 1 0
#> 24 23.89 1 38 0 0
#> 110 17.56 1 65 0 1
#> 169.2 22.41 1 46 0 0
#> 195.1 11.76 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 41 18.02 1 40 1 0
#> 129 23.41 1 53 1 0
#> 166 19.98 1 48 0 0
#> 170 19.54 1 43 0 1
#> 117.1 17.46 1 26 0 1
#> 18.1 15.21 1 49 1 0
#> 171.1 16.57 1 41 0 1
#> 180 14.82 1 37 0 0
#> 136 21.83 1 43 0 1
#> 41.1 18.02 1 40 1 0
#> 159 10.55 1 50 0 1
#> 90 20.94 1 50 0 1
#> 60 13.15 1 38 1 0
#> 77 7.27 1 67 0 1
#> 164 23.60 1 76 0 1
#> 68 20.62 1 44 0 0
#> 41.2 18.02 1 40 1 0
#> 43 12.10 1 61 0 1
#> 91.2 5.33 1 61 0 1
#> 92 22.92 1 47 0 1
#> 59.1 10.16 1 NA 1 0
#> 171.2 16.57 1 41 0 1
#> 101 9.97 1 10 0 1
#> 159.1 10.55 1 50 0 1
#> 125.1 15.65 1 67 1 0
#> 97.1 19.14 1 65 0 1
#> 180.1 14.82 1 37 0 0
#> 154.2 12.63 1 20 1 0
#> 192 16.44 1 31 1 0
#> 145 10.07 1 65 1 0
#> 90.1 20.94 1 50 0 1
#> 179.1 18.63 1 42 0 0
#> 41.3 18.02 1 40 1 0
#> 124 9.73 1 NA 1 0
#> 32.1 20.90 1 37 1 0
#> 101.1 9.97 1 10 0 1
#> 184 17.77 1 38 0 0
#> 125.2 15.65 1 67 1 0
#> 157.3 15.10 1 47 0 0
#> 91.3 5.33 1 61 0 1
#> 127 3.53 1 62 0 1
#> 151 24.00 0 42 0 0
#> 186 24.00 0 45 1 0
#> 1 24.00 0 23 1 0
#> 193 24.00 0 45 0 1
#> 119 24.00 0 17 0 0
#> 98 24.00 0 34 1 0
#> 165 24.00 0 47 0 0
#> 146 24.00 0 63 1 0
#> 135 24.00 0 58 1 0
#> 137 24.00 0 45 1 0
#> 7 24.00 0 37 1 0
#> 73 24.00 0 NA 0 1
#> 87 24.00 0 27 0 0
#> 98.1 24.00 0 34 1 0
#> 160 24.00 0 31 1 0
#> 98.2 24.00 0 34 1 0
#> 135.1 24.00 0 58 1 0
#> 173 24.00 0 19 0 1
#> 46 24.00 0 71 0 0
#> 19 24.00 0 57 0 1
#> 176 24.00 0 43 0 1
#> 176.1 24.00 0 43 0 1
#> 186.1 24.00 0 45 1 0
#> 83 24.00 0 6 0 0
#> 174 24.00 0 49 1 0
#> 12 24.00 0 63 0 0
#> 182 24.00 0 35 0 0
#> 71 24.00 0 51 0 0
#> 94 24.00 0 51 0 1
#> 138 24.00 0 44 1 0
#> 146.1 24.00 0 63 1 0
#> 9 24.00 0 31 1 0
#> 173.1 24.00 0 19 0 1
#> 3 24.00 0 31 1 0
#> 131 24.00 0 66 0 0
#> 196 24.00 0 19 0 0
#> 196.1 24.00 0 19 0 0
#> 103 24.00 0 56 1 0
#> 109 24.00 0 48 0 0
#> 67 24.00 0 25 0 0
#> 3.1 24.00 0 31 1 0
#> 132 24.00 0 55 0 0
#> 196.2 24.00 0 19 0 0
#> 156 24.00 0 50 1 0
#> 121 24.00 0 57 1 0
#> 11 24.00 0 42 0 1
#> 185 24.00 0 44 1 0
#> 137.1 24.00 0 45 1 0
#> 94.1 24.00 0 51 0 1
#> 151.1 24.00 0 42 0 0
#> 120 24.00 0 68 0 1
#> 193.1 24.00 0 45 0 1
#> 116 24.00 0 58 0 1
#> 116.1 24.00 0 58 0 1
#> 198 24.00 0 66 0 1
#> 83.1 24.00 0 6 0 0
#> 185.1 24.00 0 44 1 0
#> 165.1 24.00 0 47 0 0
#> 12.1 24.00 0 63 0 0
#> 83.2 24.00 0 6 0 0
#> 64 24.00 0 43 0 0
#> 94.2 24.00 0 51 0 1
#> 11.1 24.00 0 42 0 1
#> 193.2 24.00 0 45 0 1
#> 109.1 24.00 0 48 0 0
#> 116.2 24.00 0 58 0 1
#> 118 24.00 0 44 1 0
#> 74 24.00 0 43 0 1
#> 9.1 24.00 0 31 1 0
#> 120.1 24.00 0 68 0 1
#> 156.1 24.00 0 50 1 0
#> 65 24.00 0 57 1 0
#> 46.1 24.00 0 71 0 0
#> 163 24.00 0 66 0 0
#> 151.2 24.00 0 42 0 0
#> 160.1 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 126 24.00 0 48 0 0
#> 172 24.00 0 41 0 0
#> 73.1 24.00 0 NA 0 1
#> 75 24.00 0 21 1 0
#> 176.2 24.00 0 43 0 1
#> 33 24.00 0 53 0 0
#> 193.3 24.00 0 45 0 1
#> 34 24.00 0 36 0 0
#> 17 24.00 0 38 0 1
#> 138.1 24.00 0 44 1 0
#> 162 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.733 NA NA NA
#> 2 age, Cure model 0.0153 NA NA NA
#> 3 grade_ii, Cure model 0.234 NA NA NA
#> 4 grade_iii, Cure model 0.462 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00724 NA NA NA
#> 2 grade_ii, Survival model 0.557 NA NA NA
#> 3 grade_iii, Survival model 0.394 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.73347 0.01529 0.23421 0.46184
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 257.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.73346778 0.01528774 0.23421124 0.46183589
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.007239893 0.556948434 0.394114489
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.748216927 0.480371060 0.086564900 0.076071162 0.267853632 0.048325193
#> [7] 0.197999653 0.499137413 0.168560813 0.385331506 0.954177955 0.898604414
#> [13] 0.954177955 0.298387288 0.575123563 0.709569247 0.575123563 0.748216927
#> [19] 0.689998741 0.555910750 0.188189386 0.499137413 0.248062466 0.842471362
#> [25] 0.238021852 0.680181354 0.622811720 0.346449245 0.738526938 0.709569247
#> [31] 0.414081526 0.288036308 0.795360736 0.108156385 0.594250469 0.728819298
#> [37] 0.149332792 0.048325193 0.461471499 0.404366619 0.527580794 0.622811720
#> [43] 0.935757374 0.555910750 0.008802409 0.499137413 0.776361681 0.356182152
#> [49] 0.622811720 0.603866620 0.785840977 0.842471362 0.917118939 0.842471362
#> [55] 0.118721572 0.480371060 0.935757374 0.423745637 0.207954789 0.898604414
#> [61] 0.795360736 0.002359246 0.375582025 0.048325193 0.451890271 0.308696022
#> [67] 0.028797086 0.217899818 0.227979960 0.385331506 0.603866620 0.423745637
#> [73] 0.660782266 0.097411613 0.308696022 0.823652758 0.129242743 0.699806265
#> [79] 0.926434081 0.018343752 0.178301369 0.308696022 0.814181994 0.954177955
#> [85] 0.038622291 0.423745637 0.879968575 0.823652758 0.527580794 0.248062466
#> [91] 0.660782266 0.748216927 0.461471499 0.870524494 0.129242743 0.267853632
#> [97] 0.308696022 0.149332792 0.879968575 0.365851155 0.527580794 0.622811720
#> [103] 0.954177955 0.990728527 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 154 79 175 194 179 169 150 100 190 117 91 187 91.1
#> 12.63 16.23 21.91 22.40 18.63 22.41 20.33 16.07 20.81 17.46 5.33 9.92 5.33
#> 108 39 123 39.1 154.1 57 6 128 100.1 97 52 76 133
#> 18.29 15.59 13.00 15.59 12.63 14.46 15.64 20.35 16.07 19.14 10.42 19.22 14.65
#> 157 40 140 123.1 106 8 49 153 167 14 32 169.1 85
#> 15.10 18.00 12.68 13.00 16.67 18.43 12.19 21.33 15.55 12.89 20.90 22.41 16.44
#> 23 125 157.1 25 6.1 168 100.2 37 134 157.2 18 56 52.1
#> 16.92 15.65 15.10 6.32 15.64 23.72 16.07 12.52 17.81 15.10 15.21 12.21 10.42
#> 16 52.2 36 79.1 25.1 171 158 187.1 49.1 24 110 169.2 130
#> 8.71 10.42 21.19 16.23 6.32 16.57 20.14 9.92 12.19 23.89 17.56 22.41 16.47
#> 41 129 166 170 117.1 18.1 171.1 180 136 41.1 159 90 60
#> 18.02 23.41 19.98 19.54 17.46 15.21 16.57 14.82 21.83 18.02 10.55 20.94 13.15
#> 77 164 68 41.2 43 91.2 92 171.2 101 159.1 125.1 97.1 180.1
#> 7.27 23.60 20.62 18.02 12.10 5.33 22.92 16.57 9.97 10.55 15.65 19.14 14.82
#> 154.2 192 145 90.1 179.1 41.3 32.1 101.1 184 125.2 157.3 91.3 127
#> 12.63 16.44 10.07 20.94 18.63 18.02 20.90 9.97 17.77 15.65 15.10 5.33 3.53
#> 151 186 1 193 119 98 165 146 135 137 7 87 98.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160 98.2 135.1 173 46 19 176 176.1 186.1 83 174 12 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 94 138 146.1 9 173.1 3 131 196 196.1 103 109 67
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.1 132 196.2 156 121 11 185 137.1 94.1 151.1 120 193.1 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116.1 198 83.1 185.1 165.1 12.1 83.2 64 94.2 11.1 193.2 109.1 116.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 74 9.1 120.1 156.1 65 46.1 163 151.2 160.1 72 126 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 176.2 33 193.3 34 17 138.1 162
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[72]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.005343616 0.678972125 0.486952114
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.92766893 0.02066199 -0.23993321
#> grade_iii, Cure model
#> 0.56904051
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 195 11.76 1 NA 1 0
#> 93 10.33 1 52 0 1
#> 88 18.37 1 47 0 0
#> 179 18.63 1 42 0 0
#> 190 20.81 1 42 1 0
#> 60 13.15 1 38 1 0
#> 175 21.91 1 43 0 0
#> 16 8.71 1 71 0 1
#> 164 23.60 1 76 0 1
#> 170 19.54 1 43 0 1
#> 111 17.45 1 47 0 1
#> 189 10.51 1 NA 1 0
#> 107 11.18 1 54 1 0
#> 181 16.46 1 45 0 1
#> 100 16.07 1 60 0 0
#> 45 17.42 1 54 0 1
#> 110 17.56 1 65 0 1
#> 96 14.54 1 33 0 1
#> 107.1 11.18 1 54 1 0
#> 111.1 17.45 1 47 0 1
#> 177 12.53 1 75 0 0
#> 76 19.22 1 54 0 1
#> 25 6.32 1 34 1 0
#> 114 13.68 1 NA 0 0
#> 136 21.83 1 43 0 1
#> 66 22.13 1 53 0 0
#> 91 5.33 1 61 0 1
#> 195.1 11.76 1 NA 1 0
#> 181.1 16.46 1 45 0 1
#> 168 23.72 1 70 0 0
#> 93.1 10.33 1 52 0 1
#> 111.2 17.45 1 47 0 1
#> 187 9.92 1 39 1 0
#> 179.1 18.63 1 42 0 0
#> 136.1 21.83 1 43 0 1
#> 10 10.53 1 34 0 0
#> 85 16.44 1 36 0 0
#> 79 16.23 1 54 1 0
#> 86 23.81 1 58 0 1
#> 43 12.10 1 61 0 1
#> 195.2 11.76 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 10.1 10.53 1 34 0 0
#> 59 10.16 1 NA 1 0
#> 140 12.68 1 59 1 0
#> 69 23.23 1 25 0 1
#> 60.1 13.15 1 38 1 0
#> 105 19.75 1 60 0 0
#> 88.1 18.37 1 47 0 0
#> 24 23.89 1 38 0 0
#> 114.1 13.68 1 NA 0 0
#> 111.3 17.45 1 47 0 1
#> 42 12.43 1 49 0 1
#> 10.2 10.53 1 34 0 0
#> 180 14.82 1 37 0 0
#> 100.1 16.07 1 60 0 0
#> 169 22.41 1 46 0 0
#> 76.1 19.22 1 54 0 1
#> 55 19.34 1 69 0 1
#> 70 7.38 1 30 1 0
#> 43.1 12.10 1 61 0 1
#> 184 17.77 1 38 0 0
#> 124 9.73 1 NA 1 0
#> 96.1 14.54 1 33 0 1
#> 123 13.00 1 44 1 0
#> 50 10.02 1 NA 1 0
#> 153 21.33 1 55 1 0
#> 168.1 23.72 1 70 0 0
#> 168.2 23.72 1 70 0 0
#> 184.1 17.77 1 38 0 0
#> 24.1 23.89 1 38 0 0
#> 108 18.29 1 39 0 1
#> 26 15.77 1 49 0 1
#> 127 3.53 1 62 0 1
#> 60.2 13.15 1 38 1 0
#> 129 23.41 1 53 1 0
#> 68 20.62 1 44 0 0
#> 79.1 16.23 1 54 1 0
#> 63 22.77 1 31 1 0
#> 29 15.45 1 68 1 0
#> 61 10.12 1 36 0 1
#> 127.1 3.53 1 62 0 1
#> 189.1 10.51 1 NA 1 0
#> 158 20.14 1 74 1 0
#> 177.1 12.53 1 75 0 0
#> 56 12.21 1 60 0 0
#> 88.2 18.37 1 47 0 0
#> 153.1 21.33 1 55 1 0
#> 180.1 14.82 1 37 0 0
#> 41 18.02 1 40 1 0
#> 96.2 14.54 1 33 0 1
#> 197 21.60 1 69 1 0
#> 170.1 19.54 1 43 0 1
#> 110.1 17.56 1 65 0 1
#> 89 11.44 1 NA 0 0
#> 106 16.67 1 49 1 0
#> 26.1 15.77 1 49 0 1
#> 171 16.57 1 41 0 1
#> 110.2 17.56 1 65 0 1
#> 194 22.40 1 38 0 1
#> 187.1 9.92 1 39 1 0
#> 85.1 16.44 1 36 0 0
#> 183 9.24 1 67 1 0
#> 107.2 11.18 1 54 1 0
#> 134 17.81 1 47 1 0
#> 130 16.47 1 53 0 1
#> 49 12.19 1 48 1 0
#> 113 22.86 1 34 0 0
#> 39 15.59 1 37 0 1
#> 157 15.10 1 47 0 0
#> 199 19.81 1 NA 0 1
#> 117 17.46 1 26 0 1
#> 73 24.00 0 NA 0 1
#> 19 24.00 0 57 0 1
#> 48 24.00 0 31 1 0
#> 173 24.00 0 19 0 1
#> 3 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 172.1 24.00 0 41 0 0
#> 182 24.00 0 35 0 0
#> 131 24.00 0 66 0 0
#> 104 24.00 0 50 1 0
#> 34 24.00 0 36 0 0
#> 72 24.00 0 40 0 1
#> 83 24.00 0 6 0 0
#> 146 24.00 0 63 1 0
#> 182.1 24.00 0 35 0 0
#> 54 24.00 0 53 1 0
#> 161 24.00 0 45 0 0
#> 116 24.00 0 58 0 1
#> 138 24.00 0 44 1 0
#> 44 24.00 0 56 0 0
#> 12 24.00 0 63 0 0
#> 31 24.00 0 36 0 1
#> 47 24.00 0 38 0 1
#> 7 24.00 0 37 1 0
#> 71 24.00 0 51 0 0
#> 185 24.00 0 44 1 0
#> 146.1 24.00 0 63 1 0
#> 20 24.00 0 46 1 0
#> 65 24.00 0 57 1 0
#> 48.1 24.00 0 31 1 0
#> 144 24.00 0 28 0 1
#> 48.2 24.00 0 31 1 0
#> 198 24.00 0 66 0 1
#> 73.1 24.00 0 NA 0 1
#> 142 24.00 0 53 0 0
#> 46 24.00 0 71 0 0
#> 46.1 24.00 0 71 0 0
#> 116.1 24.00 0 58 0 1
#> 186 24.00 0 45 1 0
#> 17 24.00 0 38 0 1
#> 67 24.00 0 25 0 0
#> 185.1 24.00 0 44 1 0
#> 67.1 24.00 0 25 0 0
#> 174 24.00 0 49 1 0
#> 87 24.00 0 27 0 0
#> 84 24.00 0 39 0 1
#> 172.2 24.00 0 41 0 0
#> 20.1 24.00 0 46 1 0
#> 98 24.00 0 34 1 0
#> 62 24.00 0 71 0 0
#> 135 24.00 0 58 1 0
#> 200 24.00 0 64 0 0
#> 83.1 24.00 0 6 0 0
#> 1 24.00 0 23 1 0
#> 38 24.00 0 31 1 0
#> 67.2 24.00 0 25 0 0
#> 174.1 24.00 0 49 1 0
#> 160 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 84.1 24.00 0 39 0 1
#> 74 24.00 0 43 0 1
#> 172.3 24.00 0 41 0 0
#> 173.1 24.00 0 19 0 1
#> 12.1 24.00 0 63 0 0
#> 120 24.00 0 68 0 1
#> 112 24.00 0 61 0 0
#> 135.1 24.00 0 58 1 0
#> 160.1 24.00 0 31 1 0
#> 135.2 24.00 0 58 1 0
#> 19.1 24.00 0 57 0 1
#> 64 24.00 0 43 0 0
#> 182.2 24.00 0 35 0 0
#> 120.1 24.00 0 68 0 1
#> 135.3 24.00 0 58 1 0
#> 132 24.00 0 55 0 0
#> 148 24.00 0 61 1 0
#> 44.1 24.00 0 56 0 0
#> 165 24.00 0 47 0 0
#> 17.1 24.00 0 38 0 1
#> 126 24.00 0 48 0 0
#> 74.1 24.00 0 43 0 1
#> 95 24.00 0 68 0 1
#> 3.1 24.00 0 31 1 0
#> 185.2 24.00 0 44 1 0
#> 144.1 24.00 0 28 0 1
#> 193 24.00 0 45 0 1
#> 22 24.00 0 52 1 0
#> 118 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.928 NA NA NA
#> 2 age, Cure model 0.0207 NA NA NA
#> 3 grade_ii, Cure model -0.240 NA NA NA
#> 4 grade_iii, Cure model 0.569 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00534 NA NA NA
#> 2 grade_ii, Survival model 0.679 NA NA NA
#> 3 grade_iii, Survival model 0.487 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.92767 0.02066 -0.23993 0.56904
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.8
#> Residual Deviance: 248 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.92766893 0.02066199 -0.23993321 0.56904051
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.005343616 0.678972125 0.486952114
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.896581574 0.368809504 0.337992304 0.244324668 0.736586261 0.176761730
#> [7] 0.948799877 0.076988591 0.286900875 0.491000365 0.844158367 0.568053697
#> [13] 0.624674424 0.529273255 0.451069659 0.709104914 0.844158367 0.491000365
#> [19] 0.781419567 0.317823935 0.966020888 0.188908493 0.164784188 0.974556210
#> [25] 0.568053697 0.041685485 0.896581574 0.491000365 0.922882271 0.337992304
#> [31] 0.188908493 0.870304370 0.586949321 0.605952045 0.029262623 0.826372029
#> [37] 0.358405840 0.870304370 0.772461072 0.104073775 0.736586261 0.276219142
#> [43] 0.368809504 0.008594893 0.491000365 0.799368981 0.870304370 0.690397878
#> [49] 0.624674424 0.140947459 0.317823935 0.307427575 0.957436702 0.826372029
#> [55] 0.430736987 0.709104914 0.763456774 0.223034239 0.041685485 0.041685485
#> [61] 0.430736987 0.008594893 0.399714109 0.643552030 0.983078496 0.736586261
#> [67] 0.091016924 0.254940373 0.605952045 0.129098661 0.671682698 0.914106407
#> [73] 0.983078496 0.265649562 0.781419567 0.808368988 0.368809504 0.223034239
#> [79] 0.690397878 0.410204008 0.709104914 0.211597375 0.286900875 0.451069659
#> [85] 0.539072490 0.643552030 0.548780391 0.451069659 0.153017864 0.922882271
#> [91] 0.586949321 0.940154116 0.844158367 0.420537393 0.558435831 0.817396566
#> [97] 0.116474030 0.662290910 0.681026009 0.480924170 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 93 88 179 190 60 175 16 164 170 111 107 181 100
#> 10.33 18.37 18.63 20.81 13.15 21.91 8.71 23.60 19.54 17.45 11.18 16.46 16.07
#> 45 110 96 107.1 111.1 177 76 25 136 66 91 181.1 168
#> 17.42 17.56 14.54 11.18 17.45 12.53 19.22 6.32 21.83 22.13 5.33 16.46 23.72
#> 93.1 111.2 187 179.1 136.1 10 85 79 86 43 8 10.1 140
#> 10.33 17.45 9.92 18.63 21.83 10.53 16.44 16.23 23.81 12.10 18.43 10.53 12.68
#> 69 60.1 105 88.1 24 111.3 42 10.2 180 100.1 169 76.1 55
#> 23.23 13.15 19.75 18.37 23.89 17.45 12.43 10.53 14.82 16.07 22.41 19.22 19.34
#> 70 43.1 184 96.1 123 153 168.1 168.2 184.1 24.1 108 26 127
#> 7.38 12.10 17.77 14.54 13.00 21.33 23.72 23.72 17.77 23.89 18.29 15.77 3.53
#> 60.2 129 68 79.1 63 29 61 127.1 158 177.1 56 88.2 153.1
#> 13.15 23.41 20.62 16.23 22.77 15.45 10.12 3.53 20.14 12.53 12.21 18.37 21.33
#> 180.1 41 96.2 197 170.1 110.1 106 26.1 171 110.2 194 187.1 85.1
#> 14.82 18.02 14.54 21.60 19.54 17.56 16.67 15.77 16.57 17.56 22.40 9.92 16.44
#> 183 107.2 134 130 49 113 39 157 117 19 48 173 3
#> 9.24 11.18 17.81 16.47 12.19 22.86 15.59 15.10 17.46 24.00 24.00 24.00 24.00
#> 172 172.1 182 131 104 34 72 83 146 182.1 54 161 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 44 12 31 47 7 71 185 146.1 20 65 48.1 144
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48.2 198 142 46 46.1 116.1 186 17 67 185.1 67.1 174 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 172.2 20.1 98 62 135 200 83.1 1 38 67.2 174.1 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 84.1 74 172.3 173.1 12.1 120 112 135.1 160.1 135.2 19.1 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182.2 120.1 135.3 132 148 44.1 165 17.1 126 74.1 95 3.1 185.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144.1 193 22 118
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[73]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.001482372 1.188511147 0.973473606
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.56254273 0.02531581 0.46569612
#> grade_iii, Cure model
#> 1.08803911
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 136 21.83 1 43 0 1
#> 113 22.86 1 34 0 0
#> 88 18.37 1 47 0 0
#> 99 21.19 1 38 0 1
#> 59 10.16 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 86 23.81 1 58 0 1
#> 24 23.89 1 38 0 0
#> 13 14.34 1 54 0 1
#> 90 20.94 1 50 0 1
#> 58 19.34 1 39 0 0
#> 6 15.64 1 39 0 0
#> 187 9.92 1 39 1 0
#> 18 15.21 1 49 1 0
#> 140 12.68 1 59 1 0
#> 24.1 23.89 1 38 0 0
#> 106 16.67 1 49 1 0
#> 189 10.51 1 NA 1 0
#> 134 17.81 1 47 1 0
#> 192 16.44 1 31 1 0
#> 66 22.13 1 53 0 0
#> 39 15.59 1 37 0 1
#> 24.2 23.89 1 38 0 0
#> 52 10.42 1 52 0 1
#> 24.3 23.89 1 38 0 0
#> 168 23.72 1 70 0 0
#> 199 19.81 1 NA 0 1
#> 88.1 18.37 1 47 0 0
#> 37 12.52 1 57 1 0
#> 107 11.18 1 54 1 0
#> 14 12.89 1 21 0 0
#> 4 17.64 1 NA 0 1
#> 52.1 10.42 1 52 0 1
#> 15 22.68 1 48 0 0
#> 79 16.23 1 54 1 0
#> 49 12.19 1 48 1 0
#> 171 16.57 1 41 0 1
#> 129 23.41 1 53 1 0
#> 158 20.14 1 74 1 0
#> 93 10.33 1 52 0 1
#> 55 19.34 1 69 0 1
#> 43 12.10 1 61 0 1
#> 107.1 11.18 1 54 1 0
#> 15.1 22.68 1 48 0 0
#> 36 21.19 1 48 0 1
#> 111 17.45 1 47 0 1
#> 76 19.22 1 54 0 1
#> 168.1 23.72 1 70 0 0
#> 117 17.46 1 26 0 1
#> 124 9.73 1 NA 1 0
#> 97 19.14 1 65 0 1
#> 164 23.60 1 76 0 1
#> 51 18.23 1 83 0 1
#> 30 17.43 1 78 0 0
#> 70 7.38 1 30 1 0
#> 92 22.92 1 47 0 1
#> 29 15.45 1 68 1 0
#> 140.1 12.68 1 59 1 0
#> 127 3.53 1 62 0 1
#> 88.2 18.37 1 47 0 0
#> 13.1 14.34 1 54 0 1
#> 183 9.24 1 67 1 0
#> 167 15.55 1 56 1 0
#> 194 22.40 1 38 0 1
#> 134.1 17.81 1 47 1 0
#> 108 18.29 1 39 0 1
#> 190 20.81 1 42 1 0
#> 40 18.00 1 28 1 0
#> 63 22.77 1 31 1 0
#> 157 15.10 1 47 0 0
#> 106.1 16.67 1 49 1 0
#> 91 5.33 1 61 0 1
#> 23 16.92 1 61 0 0
#> 25 6.32 1 34 1 0
#> 140.2 12.68 1 59 1 0
#> 106.2 16.67 1 49 1 0
#> 105 19.75 1 60 0 0
#> 16 8.71 1 71 0 1
#> 96 14.54 1 33 0 1
#> 8 18.43 1 32 0 0
#> 70.1 7.38 1 30 1 0
#> 108.1 18.29 1 39 0 1
#> 127.1 3.53 1 62 0 1
#> 175 21.91 1 43 0 0
#> 171.1 16.57 1 41 0 1
#> 130 16.47 1 53 0 1
#> 52.2 10.42 1 52 0 1
#> 90.1 20.94 1 50 0 1
#> 43.1 12.10 1 61 0 1
#> 110 17.56 1 65 0 1
#> 188 16.16 1 46 0 1
#> 57 14.46 1 45 0 1
#> 60 13.15 1 38 1 0
#> 110.1 17.56 1 65 0 1
#> 181 16.46 1 45 0 1
#> 167.1 15.55 1 56 1 0
#> 57.1 14.46 1 45 0 1
#> 199.1 19.81 1 NA 0 1
#> 45 17.42 1 54 0 1
#> 96.1 14.54 1 33 0 1
#> 199.2 19.81 1 NA 0 1
#> 110.2 17.56 1 65 0 1
#> 124.1 9.73 1 NA 1 0
#> 55.1 19.34 1 69 0 1
#> 158.1 20.14 1 74 1 0
#> 168.2 23.72 1 70 0 0
#> 52.3 10.42 1 52 0 1
#> 139 21.49 1 63 1 0
#> 26 15.77 1 49 0 1
#> 128 20.35 1 35 0 1
#> 10 10.53 1 34 0 0
#> 153 21.33 1 55 1 0
#> 109 24.00 0 48 0 0
#> 35 24.00 0 51 0 0
#> 120 24.00 0 68 0 1
#> 143 24.00 0 51 0 0
#> 95 24.00 0 68 0 1
#> 132 24.00 0 55 0 0
#> 193 24.00 0 45 0 1
#> 2 24.00 0 9 0 0
#> 118 24.00 0 44 1 0
#> 165 24.00 0 47 0 0
#> 12 24.00 0 63 0 0
#> 21 24.00 0 47 0 0
#> 143.1 24.00 0 51 0 0
#> 9 24.00 0 31 1 0
#> 82 24.00 0 34 0 0
#> 44 24.00 0 56 0 0
#> 109.1 24.00 0 48 0 0
#> 53 24.00 0 32 0 1
#> 104 24.00 0 50 1 0
#> 83 24.00 0 6 0 0
#> 73 24.00 0 NA 0 1
#> 141 24.00 0 44 1 0
#> 122 24.00 0 66 0 0
#> 191 24.00 0 60 0 1
#> 112 24.00 0 61 0 0
#> 151 24.00 0 42 0 0
#> 83.1 24.00 0 6 0 0
#> 135 24.00 0 58 1 0
#> 126 24.00 0 48 0 0
#> 178 24.00 0 52 1 0
#> 9.1 24.00 0 31 1 0
#> 121 24.00 0 57 1 0
#> 163 24.00 0 66 0 0
#> 173 24.00 0 19 0 1
#> 162 24.00 0 51 0 0
#> 54 24.00 0 53 1 0
#> 19 24.00 0 57 0 1
#> 148 24.00 0 61 1 0
#> 53.1 24.00 0 32 0 1
#> 34 24.00 0 36 0 0
#> 104.1 24.00 0 50 1 0
#> 62 24.00 0 71 0 0
#> 31 24.00 0 36 0 1
#> 9.2 24.00 0 31 1 0
#> 143.2 24.00 0 51 0 0
#> 191.1 24.00 0 60 0 1
#> 7 24.00 0 37 1 0
#> 75 24.00 0 21 1 0
#> 196 24.00 0 19 0 0
#> 122.1 24.00 0 66 0 0
#> 143.3 24.00 0 51 0 0
#> 38 24.00 0 31 1 0
#> 148.1 24.00 0 61 1 0
#> 160 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 109.2 24.00 0 48 0 0
#> 178.1 24.00 0 52 1 0
#> 112.1 24.00 0 61 0 0
#> 198 24.00 0 66 0 1
#> 148.2 24.00 0 61 1 0
#> 54.1 24.00 0 53 1 0
#> 1 24.00 0 23 1 0
#> 152 24.00 0 36 0 1
#> 17 24.00 0 38 0 1
#> 176 24.00 0 43 0 1
#> 118.1 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 31.1 24.00 0 36 0 1
#> 71 24.00 0 51 0 0
#> 47 24.00 0 38 0 1
#> 173.1 24.00 0 19 0 1
#> 103 24.00 0 56 1 0
#> 82.1 24.00 0 34 0 0
#> 132.1 24.00 0 55 0 0
#> 182 24.00 0 35 0 0
#> 20 24.00 0 46 1 0
#> 73.1 24.00 0 NA 0 1
#> 191.2 24.00 0 60 0 1
#> 191.3 24.00 0 60 0 1
#> 141.1 24.00 0 44 1 0
#> 165.1 24.00 0 47 0 0
#> 75.1 24.00 0 21 1 0
#> 176.1 24.00 0 43 0 1
#> 144 24.00 0 28 0 1
#> 62.1 24.00 0 71 0 0
#> 186 24.00 0 45 1 0
#> 160.1 24.00 0 31 1 0
#> 47.1 24.00 0 38 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.56 NA NA NA
#> 2 age, Cure model 0.0253 NA NA NA
#> 3 grade_ii, Cure model 0.466 NA NA NA
#> 4 grade_iii, Cure model 1.09 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00148 NA NA NA
#> 2 grade_ii, Survival model 1.19 NA NA NA
#> 3 grade_iii, Survival model 0.973 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.56254 0.02532 0.46570 1.08804
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 246.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.56254273 0.02531581 0.46569612 1.08803911
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.001482372 1.188511147 0.973473606
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.41737322 0.30702099 0.60412091 0.45787086 0.89968558 0.15009030
#> [7] 0.05210653 0.86405131 0.48101338 0.55138757 0.80290019 0.96091246
#> [13] 0.83157675 0.88480350 0.05210653 0.73407296 0.66242441 0.77885118
#> [19] 0.38716241 0.80880888 0.05210653 0.93819281 0.05210653 0.17631445
#> [25] 0.60412091 0.90467680 0.92408762 0.87963939 0.93819281 0.34077655
#> [31] 0.78498499 0.90961310 0.75357154 0.26974210 0.52324218 0.95636757
#> [37] 0.55138757 0.91449492 0.92408762 0.34077655 0.45787086 0.70614380
#> [43] 0.57802154 0.17631445 0.69901559 0.58684088 0.24685685 0.64628349
#> [49] 0.71316785 0.97430301 0.28926125 0.82597312 0.88480350 0.99156218
#> [55] 0.60412091 0.86405131 0.96541269 0.81465327 0.37211891 0.66242441
#> [61] 0.62975362 0.50263934 0.65446085 0.32483164 0.83710396 0.73407296
#> [67] 0.98728263 0.72713335 0.98297660 0.88480350 0.73407296 0.54194173
#> [73] 0.96987193 0.84263362 0.59547799 0.97430301 0.62975362 0.99156218
#> [79] 0.40225027 0.75357154 0.76629854 0.93819281 0.48101338 0.91449492
#> [85] 0.67751255 0.79102303 0.85344164 0.87447621 0.67751255 0.77261250
#> [91] 0.81465327 0.85344164 0.72019946 0.84263362 0.67751255 0.55138757
#> [97] 0.52324218 0.17631445 0.93819281 0.43172479 0.79699395 0.51309720
#> [103] 0.93348238 0.44518617 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 136 113 88 99 177 86 24 13 90 58 6 187 18
#> 21.83 22.86 18.37 21.19 12.53 23.81 23.89 14.34 20.94 19.34 15.64 9.92 15.21
#> 140 24.1 106 134 192 66 39 24.2 52 24.3 168 88.1 37
#> 12.68 23.89 16.67 17.81 16.44 22.13 15.59 23.89 10.42 23.89 23.72 18.37 12.52
#> 107 14 52.1 15 79 49 171 129 158 93 55 43 107.1
#> 11.18 12.89 10.42 22.68 16.23 12.19 16.57 23.41 20.14 10.33 19.34 12.10 11.18
#> 15.1 36 111 76 168.1 117 97 164 51 30 70 92 29
#> 22.68 21.19 17.45 19.22 23.72 17.46 19.14 23.60 18.23 17.43 7.38 22.92 15.45
#> 140.1 127 88.2 13.1 183 167 194 134.1 108 190 40 63 157
#> 12.68 3.53 18.37 14.34 9.24 15.55 22.40 17.81 18.29 20.81 18.00 22.77 15.10
#> 106.1 91 23 25 140.2 106.2 105 16 96 8 70.1 108.1 127.1
#> 16.67 5.33 16.92 6.32 12.68 16.67 19.75 8.71 14.54 18.43 7.38 18.29 3.53
#> 175 171.1 130 52.2 90.1 43.1 110 188 57 60 110.1 181 167.1
#> 21.91 16.57 16.47 10.42 20.94 12.10 17.56 16.16 14.46 13.15 17.56 16.46 15.55
#> 57.1 45 96.1 110.2 55.1 158.1 168.2 52.3 139 26 128 10 153
#> 14.46 17.42 14.54 17.56 19.34 20.14 23.72 10.42 21.49 15.77 20.35 10.53 21.33
#> 109 35 120 143 95 132 193 2 118 165 12 21 143.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 82 44 109.1 53 104 83 141 122 191 112 151 83.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 126 178 9.1 121 163 173 162 54 19 148 53.1 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104.1 62 31 9.2 143.2 191.1 7 75 196 122.1 143.3 38 148.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160 142 109.2 178.1 112.1 198 148.2 54.1 1 152 17 176 118.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 31.1 71 47 173.1 103 82.1 132.1 182 20 191.2 191.3 141.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165.1 75.1 176.1 144 62.1 186 160.1 47.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[74]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.0003324579 0.2461070262 0.2588618887
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.409957663 0.007091382 0.305138250
#> grade_iii, Cure model
#> 0.355158281
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 92 22.92 1 47 0 1
#> 61 10.12 1 36 0 1
#> 70 7.38 1 30 1 0
#> 188 16.16 1 46 0 1
#> 110 17.56 1 65 0 1
#> 195 11.76 1 NA 1 0
#> 50 10.02 1 NA 1 0
#> 197 21.60 1 69 1 0
#> 15 22.68 1 48 0 0
#> 139 21.49 1 63 1 0
#> 40 18.00 1 28 1 0
#> 78 23.88 1 43 0 0
#> 5 16.43 1 51 0 1
#> 179 18.63 1 42 0 0
#> 190 20.81 1 42 1 0
#> 25 6.32 1 34 1 0
#> 69 23.23 1 25 0 1
#> 13 14.34 1 54 0 1
#> 180 14.82 1 37 0 0
#> 145 10.07 1 65 1 0
#> 85 16.44 1 36 0 0
#> 14 12.89 1 21 0 0
#> 15.1 22.68 1 48 0 0
#> 63 22.77 1 31 1 0
#> 199 19.81 1 NA 0 1
#> 158 20.14 1 74 1 0
#> 149 8.37 1 33 1 0
#> 192 16.44 1 31 1 0
#> 134 17.81 1 47 1 0
#> 195.1 11.76 1 NA 1 0
#> 187 9.92 1 39 1 0
#> 153 21.33 1 55 1 0
#> 43 12.10 1 61 0 1
#> 199.1 19.81 1 NA 0 1
#> 105 19.75 1 60 0 0
#> 14.1 12.89 1 21 0 0
#> 85.1 16.44 1 36 0 0
#> 154 12.63 1 20 1 0
#> 6 15.64 1 39 0 0
#> 180.1 14.82 1 37 0 0
#> 134.1 17.81 1 47 1 0
#> 153.1 21.33 1 55 1 0
#> 52 10.42 1 52 0 1
#> 70.1 7.38 1 30 1 0
#> 177 12.53 1 75 0 0
#> 125 15.65 1 67 1 0
#> 184 17.77 1 38 0 0
#> 81 14.06 1 34 0 0
#> 164 23.60 1 76 0 1
#> 42 12.43 1 49 0 1
#> 129 23.41 1 53 1 0
#> 175 21.91 1 43 0 0
#> 63.1 22.77 1 31 1 0
#> 158.1 20.14 1 74 1 0
#> 125.1 15.65 1 67 1 0
#> 40.1 18.00 1 28 1 0
#> 76 19.22 1 54 0 1
#> 50.1 10.02 1 NA 1 0
#> 158.2 20.14 1 74 1 0
#> 154.1 12.63 1 20 1 0
#> 52.1 10.42 1 52 0 1
#> 59 10.16 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 43.1 12.10 1 61 0 1
#> 117 17.46 1 26 0 1
#> 179.1 18.63 1 42 0 0
#> 79 16.23 1 54 1 0
#> 194 22.40 1 38 0 1
#> 32 20.90 1 37 1 0
#> 86 23.81 1 58 0 1
#> 127 3.53 1 62 0 1
#> 183 9.24 1 67 1 0
#> 99 21.19 1 38 0 1
#> 157 15.10 1 47 0 0
#> 158.3 20.14 1 74 1 0
#> 32.1 20.90 1 37 1 0
#> 6.1 15.64 1 39 0 0
#> 150 20.33 1 48 0 0
#> 89 11.44 1 NA 0 0
#> 23 16.92 1 61 0 0
#> 169 22.41 1 46 0 0
#> 13.1 14.34 1 54 0 1
#> 197.1 21.60 1 69 1 0
#> 23.1 16.92 1 61 0 0
#> 39 15.59 1 37 0 1
#> 158.4 20.14 1 74 1 0
#> 29 15.45 1 68 1 0
#> 63.2 22.77 1 31 1 0
#> 50.2 10.02 1 NA 1 0
#> 57 14.46 1 45 0 1
#> 114 13.68 1 NA 0 0
#> 55 19.34 1 69 0 1
#> 130 16.47 1 53 0 1
#> 183.1 9.24 1 67 1 0
#> 124 9.73 1 NA 1 0
#> 114.1 13.68 1 NA 0 0
#> 90 20.94 1 50 0 1
#> 195.2 11.76 1 NA 1 0
#> 128 20.35 1 35 0 1
#> 91.1 5.33 1 61 0 1
#> 113 22.86 1 34 0 0
#> 108 18.29 1 39 0 1
#> 29.1 15.45 1 68 1 0
#> 25.1 6.32 1 34 1 0
#> 101 9.97 1 10 0 1
#> 89.1 11.44 1 NA 0 0
#> 24 23.89 1 38 0 0
#> 128.1 20.35 1 35 0 1
#> 177.1 12.53 1 75 0 0
#> 194.1 22.40 1 38 0 1
#> 77 7.27 1 67 0 1
#> 106 16.67 1 49 1 0
#> 75 24.00 0 21 1 0
#> 17 24.00 0 38 0 1
#> 72 24.00 0 40 0 1
#> 116 24.00 0 58 0 1
#> 98 24.00 0 34 1 0
#> 173 24.00 0 19 0 1
#> 19 24.00 0 57 0 1
#> 174 24.00 0 49 1 0
#> 3 24.00 0 31 1 0
#> 38 24.00 0 31 1 0
#> 64 24.00 0 43 0 0
#> 12 24.00 0 63 0 0
#> 146 24.00 0 63 1 0
#> 122 24.00 0 66 0 0
#> 84 24.00 0 39 0 1
#> 178 24.00 0 52 1 0
#> 186 24.00 0 45 1 0
#> 44 24.00 0 56 0 0
#> 144 24.00 0 28 0 1
#> 200 24.00 0 64 0 0
#> 198 24.00 0 66 0 1
#> 54 24.00 0 53 1 0
#> 122.1 24.00 0 66 0 0
#> 7 24.00 0 37 1 0
#> 191 24.00 0 60 0 1
#> 115 24.00 0 NA 1 0
#> 103 24.00 0 56 1 0
#> 82 24.00 0 34 0 0
#> 38.1 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 118 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 54.1 24.00 0 53 1 0
#> 3.1 24.00 0 31 1 0
#> 38.2 24.00 0 31 1 0
#> 2 24.00 0 9 0 0
#> 143 24.00 0 51 0 0
#> 73 24.00 0 NA 0 1
#> 17.1 24.00 0 38 0 1
#> 186.1 24.00 0 45 1 0
#> 53 24.00 0 32 0 1
#> 82.1 24.00 0 34 0 0
#> 65 24.00 0 57 1 0
#> 200.1 24.00 0 64 0 0
#> 33 24.00 0 53 0 0
#> 47 24.00 0 38 0 1
#> 147 24.00 0 76 1 0
#> 141 24.00 0 44 1 0
#> 104 24.00 0 50 1 0
#> 165 24.00 0 47 0 0
#> 112 24.00 0 61 0 0
#> 34 24.00 0 36 0 0
#> 12.1 24.00 0 63 0 0
#> 143.1 24.00 0 51 0 0
#> 142 24.00 0 53 0 0
#> 152 24.00 0 36 0 1
#> 163 24.00 0 66 0 0
#> 146.1 24.00 0 63 1 0
#> 11 24.00 0 42 0 1
#> 122.2 24.00 0 66 0 0
#> 94 24.00 0 51 0 1
#> 151 24.00 0 42 0 0
#> 74 24.00 0 43 0 1
#> 67 24.00 0 25 0 0
#> 104.1 24.00 0 50 1 0
#> 74.1 24.00 0 43 0 1
#> 126 24.00 0 48 0 0
#> 74.2 24.00 0 43 0 1
#> 71 24.00 0 51 0 0
#> 11.1 24.00 0 42 0 1
#> 198.1 24.00 0 66 0 1
#> 191.1 24.00 0 60 0 1
#> 131 24.00 0 66 0 0
#> 73.1 24.00 0 NA 0 1
#> 118.1 24.00 0 44 1 0
#> 21 24.00 0 47 0 0
#> 72.1 24.00 0 40 0 1
#> 174.1 24.00 0 49 1 0
#> 73.2 24.00 0 NA 0 1
#> 185 24.00 0 44 1 0
#> 72.2 24.00 0 40 0 1
#> 98.1 24.00 0 34 1 0
#> 141.1 24.00 0 44 1 0
#> 137 24.00 0 45 1 0
#> 95 24.00 0 68 0 1
#> 98.2 24.00 0 34 1 0
#> 53.1 24.00 0 32 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.410 NA NA NA
#> 2 age, Cure model 0.00709 NA NA NA
#> 3 grade_ii, Cure model 0.305 NA NA NA
#> 4 grade_iii, Cure model 0.355 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000332 NA NA NA
#> 2 grade_ii, Survival model 0.246 NA NA NA
#> 3 grade_iii, Survival model 0.259 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.409958 0.007091 0.305138 0.355158
#>
#> Degrees of Freedom: 181 Total (i.e. Null); 178 Residual
#> Null Deviance: 251.2
#> Residual Deviance: 249.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.409957663 0.007091382 0.305138250 0.355158281
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.0003324579 0.2461070262 0.2588618887
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.11313337 0.87406223 0.93355966 0.64476209 0.54290240 0.24828584
#> [7] 0.17614268 0.27105768 0.49549313 0.03051309 0.62638826 0.46637413
#> [13] 0.34763965 0.95865258 0.09862141 0.75215320 0.72551372 0.88265055
#> [19] 0.59904558 0.77852702 0.17614268 0.14101735 0.38924356 0.92511762
#> [25] 0.59904558 0.51454903 0.89975145 0.28254252 0.83966366 0.43676006
#> [31] 0.77852702 0.59904558 0.79607273 0.67185921 0.72551372 0.51454903
#> [37] 0.28254252 0.85691783 0.93355966 0.81350794 0.65388802 0.53339621
#> [43] 0.76970279 0.06736819 0.83093374 0.08343042 0.23627888 0.14101735
#> [49] 0.38924356 0.65388802 0.49549313 0.45657165 0.38924356 0.79607273
#> [55] 0.85691783 0.97524082 0.83966366 0.55235501 0.46637413 0.63559524
#> [61] 0.21285866 0.32652736 0.04997227 0.99173871 0.90826571 0.30451688
#> [67] 0.71658291 0.38924356 0.32652736 0.67185921 0.37882444 0.56175827
#> [73] 0.20036779 0.75215320 0.24828584 0.56175827 0.68982415 0.38924356
#> [79] 0.69882912 0.14101735 0.74326007 0.44670160 0.58974366 0.90826571
#> [85] 0.31558295 0.35826384 0.97524082 0.12708328 0.48576184 0.69882912
#> [91] 0.95865258 0.89121329 0.01136695 0.35826384 0.81350794 0.21285866
#> [97] 0.95027956 0.58039478 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000
#>
#> $Time
#> 92 61 70 188 110 197 15 139 40 78 5 179 190
#> 22.92 10.12 7.38 16.16 17.56 21.60 22.68 21.49 18.00 23.88 16.43 18.63 20.81
#> 25 69 13 180 145 85 14 15.1 63 158 149 192 134
#> 6.32 23.23 14.34 14.82 10.07 16.44 12.89 22.68 22.77 20.14 8.37 16.44 17.81
#> 187 153 43 105 14.1 85.1 154 6 180.1 134.1 153.1 52 70.1
#> 9.92 21.33 12.10 19.75 12.89 16.44 12.63 15.64 14.82 17.81 21.33 10.42 7.38
#> 177 125 184 81 164 42 129 175 63.1 158.1 125.1 40.1 76
#> 12.53 15.65 17.77 14.06 23.60 12.43 23.41 21.91 22.77 20.14 15.65 18.00 19.22
#> 158.2 154.1 52.1 91 43.1 117 179.1 79 194 32 86 127 183
#> 20.14 12.63 10.42 5.33 12.10 17.46 18.63 16.23 22.40 20.90 23.81 3.53 9.24
#> 99 157 158.3 32.1 6.1 150 23 169 13.1 197.1 23.1 39 158.4
#> 21.19 15.10 20.14 20.90 15.64 20.33 16.92 22.41 14.34 21.60 16.92 15.59 20.14
#> 29 63.2 57 55 130 183.1 90 128 91.1 113 108 29.1 25.1
#> 15.45 22.77 14.46 19.34 16.47 9.24 20.94 20.35 5.33 22.86 18.29 15.45 6.32
#> 101 24 128.1 177.1 194.1 77 106 75 17 72 116 98 173
#> 9.97 23.89 20.35 12.53 22.40 7.27 16.67 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 174 3 38 64 12 146 122 84 178 186 44 144
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 198 54 122.1 7 191 103 82 38.1 9 172 118 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54.1 3.1 38.2 2 143 17.1 186.1 53 82.1 65 200.1 33 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 141 104 165 112 34 12.1 143.1 142 152 163 146.1 11
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122.2 94 151 74 67 104.1 74.1 126 74.2 71 11.1 198.1 191.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 118.1 21 72.1 174.1 185 72.2 98.1 141.1 137 95 98.2 53.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[75]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.004478984 1.042756660 0.434804463
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.409491747 0.011459203 0.009002254
#> grade_iii, Cure model
#> 0.209550844
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 24 23.89 1 38 0 0
#> 199 19.81 1 NA 0 1
#> 10 10.53 1 34 0 0
#> 63 22.77 1 31 1 0
#> 180 14.82 1 37 0 0
#> 170 19.54 1 43 0 1
#> 179 18.63 1 42 0 0
#> 55 19.34 1 69 0 1
#> 93 10.33 1 52 0 1
#> 24.1 23.89 1 38 0 0
#> 157 15.10 1 47 0 0
#> 23 16.92 1 61 0 0
#> 199.1 19.81 1 NA 0 1
#> 105 19.75 1 60 0 0
#> 45 17.42 1 54 0 1
#> 26 15.77 1 49 0 1
#> 158 20.14 1 74 1 0
#> 100 16.07 1 60 0 0
#> 29 15.45 1 68 1 0
#> 45.1 17.42 1 54 0 1
#> 127 3.53 1 62 0 1
#> 92 22.92 1 47 0 1
#> 184 17.77 1 38 0 0
#> 130 16.47 1 53 0 1
#> 194 22.40 1 38 0 1
#> 70 7.38 1 30 1 0
#> 92.1 22.92 1 47 0 1
#> 183 9.24 1 67 1 0
#> 167 15.55 1 56 1 0
#> 105.1 19.75 1 60 0 0
#> 183.1 9.24 1 67 1 0
#> 117 17.46 1 26 0 1
#> 180.1 14.82 1 37 0 0
#> 26.1 15.77 1 49 0 1
#> 60 13.15 1 38 1 0
#> 170.1 19.54 1 43 0 1
#> 78 23.88 1 43 0 0
#> 192 16.44 1 31 1 0
#> 134 17.81 1 47 1 0
#> 101 9.97 1 10 0 1
#> 168 23.72 1 70 0 0
#> 145 10.07 1 65 1 0
#> 169 22.41 1 46 0 0
#> 66 22.13 1 53 0 0
#> 168.1 23.72 1 70 0 0
#> 159 10.55 1 50 0 1
#> 157.1 15.10 1 47 0 0
#> 23.1 16.92 1 61 0 0
#> 179.1 18.63 1 42 0 0
#> 194.1 22.40 1 38 0 1
#> 159.1 10.55 1 50 0 1
#> 175 21.91 1 43 0 0
#> 149 8.37 1 33 1 0
#> 37 12.52 1 57 1 0
#> 56 12.21 1 60 0 0
#> 18 15.21 1 49 1 0
#> 91 5.33 1 61 0 1
#> 99 21.19 1 38 0 1
#> 45.2 17.42 1 54 0 1
#> 192.1 16.44 1 31 1 0
#> 56.1 12.21 1 60 0 0
#> 158.1 20.14 1 74 1 0
#> 26.2 15.77 1 49 0 1
#> 29.1 15.45 1 68 1 0
#> 192.2 16.44 1 31 1 0
#> 56.2 12.21 1 60 0 0
#> 91.1 5.33 1 61 0 1
#> 188 16.16 1 46 0 1
#> 92.2 22.92 1 47 0 1
#> 183.2 9.24 1 67 1 0
#> 194.2 22.40 1 38 0 1
#> 26.3 15.77 1 49 0 1
#> 81 14.06 1 34 0 0
#> 133 14.65 1 57 0 0
#> 155 13.08 1 26 0 0
#> 79 16.23 1 54 1 0
#> 24.2 23.89 1 38 0 0
#> 57 14.46 1 45 0 1
#> 66.1 22.13 1 53 0 0
#> 189 10.51 1 NA 1 0
#> 188.1 16.16 1 46 0 1
#> 113 22.86 1 34 0 0
#> 179.2 18.63 1 42 0 0
#> 26.4 15.77 1 49 0 1
#> 90 20.94 1 50 0 1
#> 140 12.68 1 59 1 0
#> 6 15.64 1 39 0 0
#> 90.1 20.94 1 50 0 1
#> 50 10.02 1 NA 1 0
#> 179.3 18.63 1 42 0 0
#> 99.1 21.19 1 38 0 1
#> 23.2 16.92 1 61 0 0
#> 58 19.34 1 39 0 0
#> 114 13.68 1 NA 0 0
#> 14 12.89 1 21 0 0
#> 13 14.34 1 54 0 1
#> 60.1 13.15 1 38 1 0
#> 107 11.18 1 54 1 0
#> 78.1 23.88 1 43 0 0
#> 108 18.29 1 39 0 1
#> 45.3 17.42 1 54 0 1
#> 23.3 16.92 1 61 0 0
#> 60.2 13.15 1 38 1 0
#> 81.1 14.06 1 34 0 0
#> 5 16.43 1 51 0 1
#> 136 21.83 1 43 0 1
#> 18.1 15.21 1 49 1 0
#> 159.2 10.55 1 50 0 1
#> 167.1 15.55 1 56 1 0
#> 81.2 14.06 1 34 0 0
#> 168.2 23.72 1 70 0 0
#> 134.1 17.81 1 47 1 0
#> 87 24.00 0 27 0 0
#> 47 24.00 0 38 0 1
#> 74 24.00 0 43 0 1
#> 84 24.00 0 39 0 1
#> 200 24.00 0 64 0 0
#> 84.1 24.00 0 39 0 1
#> 72 24.00 0 40 0 1
#> 109 24.00 0 48 0 0
#> 48 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 131 24.00 0 66 0 0
#> 80 24.00 0 41 0 0
#> 126 24.00 0 48 0 0
#> 135 24.00 0 58 1 0
#> 54 24.00 0 53 1 0
#> 193 24.00 0 45 0 1
#> 143 24.00 0 51 0 0
#> 135.1 24.00 0 58 1 0
#> 65 24.00 0 57 1 0
#> 118 24.00 0 44 1 0
#> 22 24.00 0 52 1 0
#> 22.1 24.00 0 52 1 0
#> 46 24.00 0 71 0 0
#> 71 24.00 0 51 0 0
#> 151 24.00 0 42 0 0
#> 198 24.00 0 66 0 1
#> 94 24.00 0 51 0 1
#> 19 24.00 0 57 0 1
#> 75 24.00 0 21 1 0
#> 146 24.00 0 63 1 0
#> 121 24.00 0 57 1 0
#> 95 24.00 0 68 0 1
#> 162 24.00 0 51 0 0
#> 65.1 24.00 0 57 1 0
#> 11 24.00 0 42 0 1
#> 163 24.00 0 66 0 0
#> 131.1 24.00 0 66 0 0
#> 84.2 24.00 0 39 0 1
#> 143.1 24.00 0 51 0 0
#> 143.2 24.00 0 51 0 0
#> 74.1 24.00 0 43 0 1
#> 38 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 3 24.00 0 31 1 0
#> 72.1 24.00 0 40 0 1
#> 191 24.00 0 60 0 1
#> 185 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 182 24.00 0 35 0 0
#> 12 24.00 0 63 0 0
#> 83 24.00 0 6 0 0
#> 83.1 24.00 0 6 0 0
#> 84.3 24.00 0 39 0 1
#> 119 24.00 0 17 0 0
#> 198.1 24.00 0 66 0 1
#> 109.1 24.00 0 48 0 0
#> 144 24.00 0 28 0 1
#> 118.1 24.00 0 44 1 0
#> 122 24.00 0 66 0 0
#> 109.2 24.00 0 48 0 0
#> 161 24.00 0 45 0 0
#> 103 24.00 0 56 1 0
#> 185.1 24.00 0 44 1 0
#> 65.2 24.00 0 57 1 0
#> 137 24.00 0 45 1 0
#> 67 24.00 0 25 0 0
#> 126.1 24.00 0 48 0 0
#> 144.1 24.00 0 28 0 1
#> 191.1 24.00 0 60 0 1
#> 142 24.00 0 53 0 0
#> 62 24.00 0 71 0 0
#> 174 24.00 0 49 1 0
#> 186 24.00 0 45 1 0
#> 162.1 24.00 0 51 0 0
#> 11.1 24.00 0 42 0 1
#> 193.1 24.00 0 45 0 1
#> 115 24.00 0 NA 1 0
#> 74.2 24.00 0 43 0 1
#> 126.2 24.00 0 48 0 0
#> 109.3 24.00 0 48 0 0
#> 162.2 24.00 0 51 0 0
#> 116 24.00 0 58 0 1
#> 31 24.00 0 36 0 1
#> 11.2 24.00 0 42 0 1
#> 11.3 24.00 0 42 0 1
#> 196 24.00 0 19 0 0
#> 144.2 24.00 0 28 0 1
#> 35 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.409 NA NA NA
#> 2 age, Cure model 0.0115 NA NA NA
#> 3 grade_ii, Cure model 0.00900 NA NA NA
#> 4 grade_iii, Cure model 0.210 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00448 NA NA NA
#> 2 grade_ii, Survival model 1.04 NA NA NA
#> 3 grade_iii, Survival model 0.435 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.409492 0.011459 0.009002 0.209551
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 266.9
#> Residual Deviance: 265.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.409491747 0.011459203 0.009002254 0.209550844
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.004478984 1.042756660 0.434804463
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.05305502 0.94372508 0.29748364 0.82688506 0.50271968 0.53996532
#> [7] 0.52155767 0.94869786 0.05305502 0.81556630 0.64875994 0.48324496
#> [13] 0.61791769 0.74196192 0.46352537 0.73523373 0.79243367 0.61791769
#> [19] 0.99550080 0.23197531 0.60130258 0.67914864 0.32746842 0.98191688
#> [25] 0.23197531 0.96338556 0.78013640 0.48324496 0.96338556 0.60965176
#> [31] 0.82688506 0.74196192 0.87162416 0.50271968 0.12332517 0.68679335
#> [37] 0.58467761 0.95852340 0.17229247 0.95364600 0.31255821 0.36602372
#> [43] 0.17229247 0.92887241 0.81556630 0.64875994 0.53996532 0.32746842
#> [49] 0.92887241 0.39170981 0.97730517 0.90337080 0.90852472 0.80421062
#> [55] 0.98648048 0.41729498 0.61791769 0.68679335 0.90852472 0.46352537
#> [61] 0.74196192 0.79243367 0.68679335 0.90852472 0.98648048 0.72180119
#> [67] 0.23197531 0.96338556 0.32746842 0.74196192 0.85503369 0.83817597
#> [73] 0.88750045 0.71493814 0.05305502 0.84382945 0.36602372 0.72180119
#> [79] 0.28046058 0.53996532 0.74196192 0.44097444 0.89813739 0.77369357
#> [85] 0.44097444 0.53996532 0.41729498 0.64875994 0.52155767 0.89282048
#> [91] 0.84944944 0.87162416 0.92381915 0.12332517 0.57565904 0.61791769
#> [97] 0.64875994 0.87162416 0.85503369 0.70789849 0.40467880 0.80421062
#> [103] 0.92887241 0.78013640 0.85503369 0.17229247 0.58467761 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000 0.00000000
#>
#> $Time
#> 24 10 63 180 170 179 55 93 24.1 157 23 105 45
#> 23.89 10.53 22.77 14.82 19.54 18.63 19.34 10.33 23.89 15.10 16.92 19.75 17.42
#> 26 158 100 29 45.1 127 92 184 130 194 70 92.1 183
#> 15.77 20.14 16.07 15.45 17.42 3.53 22.92 17.77 16.47 22.40 7.38 22.92 9.24
#> 167 105.1 183.1 117 180.1 26.1 60 170.1 78 192 134 101 168
#> 15.55 19.75 9.24 17.46 14.82 15.77 13.15 19.54 23.88 16.44 17.81 9.97 23.72
#> 145 169 66 168.1 159 157.1 23.1 179.1 194.1 159.1 175 149 37
#> 10.07 22.41 22.13 23.72 10.55 15.10 16.92 18.63 22.40 10.55 21.91 8.37 12.52
#> 56 18 91 99 45.2 192.1 56.1 158.1 26.2 29.1 192.2 56.2 91.1
#> 12.21 15.21 5.33 21.19 17.42 16.44 12.21 20.14 15.77 15.45 16.44 12.21 5.33
#> 188 92.2 183.2 194.2 26.3 81 133 155 79 24.2 57 66.1 188.1
#> 16.16 22.92 9.24 22.40 15.77 14.06 14.65 13.08 16.23 23.89 14.46 22.13 16.16
#> 113 179.2 26.4 90 140 6 90.1 179.3 99.1 23.2 58 14 13
#> 22.86 18.63 15.77 20.94 12.68 15.64 20.94 18.63 21.19 16.92 19.34 12.89 14.34
#> 60.1 107 78.1 108 45.3 23.3 60.2 81.1 5 136 18.1 159.2 167.1
#> 13.15 11.18 23.88 18.29 17.42 16.92 13.15 14.06 16.43 21.83 15.21 10.55 15.55
#> 81.2 168.2 134.1 87 47 74 84 200 84.1 72 109 48 172
#> 14.06 23.72 17.81 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 80 126 135 54 193 143 135.1 65 118 22 22.1 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 151 198 94 19 75 146 121 95 162 65.1 11 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.1 84.2 143.1 143.2 74.1 38 1 3 72.1 191 185 112 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 83 83.1 84.3 119 198.1 109.1 144 118.1 122 109.2 161 103
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185.1 65.2 137 67 126.1 144.1 191.1 142 62 174 186 162.1 11.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193.1 74.2 126.2 109.3 162.2 116 31 11.2 11.3 196 144.2 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[76]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.007950304 0.335502739 0.359759634
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.65450048 0.01260863 0.04318194
#> grade_iii, Cure model
#> 0.98873445
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 154 12.63 1 20 1 0
#> 59 10.16 1 NA 1 0
#> 199 19.81 1 NA 0 1
#> 167 15.55 1 56 1 0
#> 181 16.46 1 45 0 1
#> 92 22.92 1 47 0 1
#> 133 14.65 1 57 0 0
#> 158 20.14 1 74 1 0
#> 14 12.89 1 21 0 0
#> 139 21.49 1 63 1 0
#> 136 21.83 1 43 0 1
#> 99 21.19 1 38 0 1
#> 85 16.44 1 36 0 0
#> 45 17.42 1 54 0 1
#> 5 16.43 1 51 0 1
#> 125 15.65 1 67 1 0
#> 188 16.16 1 46 0 1
#> 24 23.89 1 38 0 0
#> 50 10.02 1 NA 1 0
#> 76 19.22 1 54 0 1
#> 139.1 21.49 1 63 1 0
#> 4 17.64 1 NA 0 1
#> 183 9.24 1 67 1 0
#> 59.1 10.16 1 NA 1 0
#> 43 12.10 1 61 0 1
#> 105 19.75 1 60 0 0
#> 127 3.53 1 62 0 1
#> 90 20.94 1 50 0 1
#> 57 14.46 1 45 0 1
#> 70 7.38 1 30 1 0
#> 50.1 10.02 1 NA 1 0
#> 188.1 16.16 1 46 0 1
#> 175 21.91 1 43 0 0
#> 79 16.23 1 54 1 0
#> 81 14.06 1 34 0 0
#> 88 18.37 1 47 0 0
#> 183.1 9.24 1 67 1 0
#> 79.1 16.23 1 54 1 0
#> 23 16.92 1 61 0 0
#> 113 22.86 1 34 0 0
#> 56 12.21 1 60 0 0
#> 199.1 19.81 1 NA 0 1
#> 153 21.33 1 55 1 0
#> 170 19.54 1 43 0 1
#> 113.1 22.86 1 34 0 0
#> 113.2 22.86 1 34 0 0
#> 123 13.00 1 44 1 0
#> 86 23.81 1 58 0 1
#> 127.1 3.53 1 62 0 1
#> 40 18.00 1 28 1 0
#> 192 16.44 1 31 1 0
#> 61 10.12 1 36 0 1
#> 133.1 14.65 1 57 0 0
#> 145 10.07 1 65 1 0
#> 106 16.67 1 49 1 0
#> 175.1 21.91 1 43 0 0
#> 42 12.43 1 49 0 1
#> 63 22.77 1 31 1 0
#> 61.1 10.12 1 36 0 1
#> 187 9.92 1 39 1 0
#> 85.1 16.44 1 36 0 0
#> 61.2 10.12 1 36 0 1
#> 63.1 22.77 1 31 1 0
#> 188.2 16.16 1 46 0 1
#> 79.2 16.23 1 54 1 0
#> 188.3 16.16 1 46 0 1
#> 10 10.53 1 34 0 0
#> 8 18.43 1 32 0 0
#> 29 15.45 1 68 1 0
#> 125.1 15.65 1 67 1 0
#> 157 15.10 1 47 0 0
#> 139.2 21.49 1 63 1 0
#> 56.1 12.21 1 60 0 0
#> 40.1 18.00 1 28 1 0
#> 158.1 20.14 1 74 1 0
#> 40.2 18.00 1 28 1 0
#> 49 12.19 1 48 1 0
#> 43.1 12.10 1 61 0 1
#> 97 19.14 1 65 0 1
#> 184 17.77 1 38 0 0
#> 129 23.41 1 53 1 0
#> 59.2 10.16 1 NA 1 0
#> 169 22.41 1 46 0 0
#> 68 20.62 1 44 0 0
#> 60 13.15 1 38 1 0
#> 179 18.63 1 42 0 0
#> 30 17.43 1 78 0 0
#> 136.1 21.83 1 43 0 1
#> 13 14.34 1 54 0 1
#> 175.2 21.91 1 43 0 0
#> 105.1 19.75 1 60 0 0
#> 171 16.57 1 41 0 1
#> 169.1 22.41 1 46 0 0
#> 37 12.52 1 57 1 0
#> 153.1 21.33 1 55 1 0
#> 170.1 19.54 1 43 0 1
#> 113.3 22.86 1 34 0 0
#> 77 7.27 1 67 0 1
#> 90.1 20.94 1 50 0 1
#> 88.1 18.37 1 47 0 0
#> 136.2 21.83 1 43 0 1
#> 179.1 18.63 1 42 0 0
#> 199.2 19.81 1 NA 0 1
#> 6 15.64 1 39 0 0
#> 42.1 12.43 1 49 0 1
#> 199.3 19.81 1 NA 0 1
#> 10.1 10.53 1 34 0 0
#> 32 20.90 1 37 1 0
#> 171.1 16.57 1 41 0 1
#> 187.1 9.92 1 39 1 0
#> 167.1 15.55 1 56 1 0
#> 197 21.60 1 69 1 0
#> 71 24.00 0 51 0 0
#> 31 24.00 0 36 0 1
#> 115 24.00 0 NA 1 0
#> 84 24.00 0 39 0 1
#> 64 24.00 0 43 0 0
#> 156 24.00 0 50 1 0
#> 19 24.00 0 57 0 1
#> 200 24.00 0 64 0 0
#> 147 24.00 0 76 1 0
#> 200.1 24.00 0 64 0 0
#> 38 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 82 24.00 0 34 0 0
#> 20 24.00 0 46 1 0
#> 152 24.00 0 36 0 1
#> 138 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 3 24.00 0 31 1 0
#> 35 24.00 0 51 0 0
#> 174 24.00 0 49 1 0
#> 138.1 24.00 0 44 1 0
#> 161 24.00 0 45 0 0
#> 142 24.00 0 53 0 0
#> 185 24.00 0 44 1 0
#> 185.1 24.00 0 44 1 0
#> 191 24.00 0 60 0 1
#> 94 24.00 0 51 0 1
#> 196 24.00 0 19 0 0
#> 126 24.00 0 48 0 0
#> 141 24.00 0 44 1 0
#> 174.1 24.00 0 49 1 0
#> 143 24.00 0 51 0 0
#> 161.1 24.00 0 45 0 0
#> 83 24.00 0 6 0 0
#> 11 24.00 0 42 0 1
#> 71.1 24.00 0 51 0 0
#> 98 24.00 0 34 1 0
#> 27 24.00 0 63 1 0
#> 186 24.00 0 45 1 0
#> 21 24.00 0 47 0 0
#> 82.1 24.00 0 34 0 0
#> 112 24.00 0 61 0 0
#> 162 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 193 24.00 0 45 0 1
#> 156.1 24.00 0 50 1 0
#> 185.2 24.00 0 44 1 0
#> 162.1 24.00 0 51 0 0
#> 126.1 24.00 0 48 0 0
#> 54 24.00 0 53 1 0
#> 141.1 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 46 24.00 0 71 0 0
#> 185.3 24.00 0 44 1 0
#> 75 24.00 0 21 1 0
#> 54.1 24.00 0 53 1 0
#> 53 24.00 0 32 0 1
#> 174.2 24.00 0 49 1 0
#> 147.1 24.00 0 76 1 0
#> 147.2 24.00 0 76 1 0
#> 48 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 72 24.00 0 40 0 1
#> 200.2 24.00 0 64 0 0
#> 73 24.00 0 NA 0 1
#> 193.1 24.00 0 45 0 1
#> 147.3 24.00 0 76 1 0
#> 67.1 24.00 0 25 0 0
#> 75.1 24.00 0 21 1 0
#> 19.1 24.00 0 57 0 1
#> 178 24.00 0 52 1 0
#> 174.3 24.00 0 49 1 0
#> 98.1 24.00 0 34 1 0
#> 172 24.00 0 41 0 0
#> 126.2 24.00 0 48 0 0
#> 109 24.00 0 48 0 0
#> 132.1 24.00 0 55 0 0
#> 38.1 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 64.1 24.00 0 43 0 0
#> 121 24.00 0 57 1 0
#> 109.1 24.00 0 48 0 0
#> 73.1 24.00 0 NA 0 1
#> 161.2 24.00 0 45 0 0
#> 75.2 24.00 0 21 1 0
#> 151 24.00 0 42 0 0
#> 103 24.00 0 56 1 0
#> 17 24.00 0 38 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.655 NA NA NA
#> 2 age, Cure model 0.0126 NA NA NA
#> 3 grade_ii, Cure model 0.0432 NA NA NA
#> 4 grade_iii, Cure model 0.989 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00795 NA NA NA
#> 2 grade_ii, Survival model 0.336 NA NA NA
#> 3 grade_iii, Survival model 0.360 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.65450 0.01261 0.04318 0.98873
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.7
#> Residual Deviance: 248.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.65450048 0.01260863 0.04318194 0.98873445
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.007950304 0.335502739 0.359759634
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.87330193 0.80019886 0.69943112 0.16480466 0.82508812 0.51362696
#> [7] 0.86736792 0.41091599 0.36023372 0.46450868 0.70666086 0.66225797
#> [13] 0.72781786 0.78103633 0.75512367 0.05019679 0.56637069 0.41091599
#> [19] 0.96856050 0.91370159 0.53163781 0.98968241 0.47484652 0.83730699
#> [25] 0.97914959 0.75512367 0.31751304 0.73486044 0.84942494 0.60753506
#> [31] 0.96856050 0.73486044 0.66986707 0.18722822 0.89658507 0.44363202
#> [37] 0.54928334 0.18722822 0.18722822 0.86142652 0.10513095 0.98968241
#> [43] 0.62354747 0.70666086 0.93599062 0.82508812 0.95236231 0.67742261
#> [49] 0.31751304 0.88507132 0.25420157 0.93599062 0.95780889 0.70666086
#> [55] 0.93599062 0.25420157 0.75512367 0.73486044 0.75512367 0.92486694
#> [61] 0.59937734 0.81269704 0.78103633 0.81890320 0.41091599 0.89658507
#> [67] 0.62354747 0.51362696 0.62354747 0.90800914 0.91370159 0.57482541
#> [73] 0.64674783 0.13852533 0.28662612 0.50402526 0.85544450 0.58310925
#> [79] 0.65454237 0.36023372 0.84339211 0.31751304 0.53163781 0.68488947
#> [85] 0.28662612 0.87921027 0.44363202 0.54928334 0.18722822 0.98443630
#> [91] 0.47484652 0.60753506 0.36023372 0.58310925 0.79380660 0.88507132
#> [97] 0.92486694 0.49434634 0.68488947 0.95780889 0.80019886 0.39836501
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 154 167 181 92 133 158 14 139 136 99 85 45 5
#> 12.63 15.55 16.46 22.92 14.65 20.14 12.89 21.49 21.83 21.19 16.44 17.42 16.43
#> 125 188 24 76 139.1 183 43 105 127 90 57 70 188.1
#> 15.65 16.16 23.89 19.22 21.49 9.24 12.10 19.75 3.53 20.94 14.46 7.38 16.16
#> 175 79 81 88 183.1 79.1 23 113 56 153 170 113.1 113.2
#> 21.91 16.23 14.06 18.37 9.24 16.23 16.92 22.86 12.21 21.33 19.54 22.86 22.86
#> 123 86 127.1 40 192 61 133.1 145 106 175.1 42 63 61.1
#> 13.00 23.81 3.53 18.00 16.44 10.12 14.65 10.07 16.67 21.91 12.43 22.77 10.12
#> 187 85.1 61.2 63.1 188.2 79.2 188.3 10 8 29 125.1 157 139.2
#> 9.92 16.44 10.12 22.77 16.16 16.23 16.16 10.53 18.43 15.45 15.65 15.10 21.49
#> 56.1 40.1 158.1 40.2 49 43.1 97 184 129 169 68 60 179
#> 12.21 18.00 20.14 18.00 12.19 12.10 19.14 17.77 23.41 22.41 20.62 13.15 18.63
#> 30 136.1 13 175.2 105.1 171 169.1 37 153.1 170.1 113.3 77 90.1
#> 17.43 21.83 14.34 21.91 19.75 16.57 22.41 12.52 21.33 19.54 22.86 7.27 20.94
#> 88.1 136.2 179.1 6 42.1 10.1 32 171.1 187.1 167.1 197 71 31
#> 18.37 21.83 18.63 15.64 12.43 10.53 20.90 16.57 9.92 15.55 21.60 24.00 24.00
#> 84 64 156 19 200 147 200.1 38 119 82 20 152 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 3 35 174 138.1 161 142 185 185.1 191 94 196 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 174.1 143 161.1 83 11 71.1 98 27 186 21 82.1 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 44 193 156.1 185.2 162.1 126.1 54 141.1 132 46 185.3 75
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54.1 53 174.2 147.1 147.2 48 67 72 200.2 193.1 147.3 67.1 75.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19.1 178 174.3 98.1 172 126.2 109 132.1 38.1 7 64.1 121 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161.2 75.2 151 103 17
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[77]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.0009680565 0.6644209865 0.4230261249
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.028819418 -0.006500673 0.648164130
#> grade_iii, Cure model
#> 0.900681490
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 99 21.19 1 38 0 1
#> 107 11.18 1 54 1 0
#> 175 21.91 1 43 0 0
#> 106 16.67 1 49 1 0
#> 187 9.92 1 39 1 0
#> 117 17.46 1 26 0 1
#> 78 23.88 1 43 0 0
#> 97 19.14 1 65 0 1
#> 58 19.34 1 39 0 0
#> 127 3.53 1 62 0 1
#> 99.1 21.19 1 38 0 1
#> 68 20.62 1 44 0 0
#> 52 10.42 1 52 0 1
#> 127.1 3.53 1 62 0 1
#> 149 8.37 1 33 1 0
#> 169 22.41 1 46 0 0
#> 105 19.75 1 60 0 0
#> 18 15.21 1 49 1 0
#> 114 13.68 1 NA 0 0
#> 155 13.08 1 26 0 0
#> 187.1 9.92 1 39 1 0
#> 85 16.44 1 36 0 0
#> 41 18.02 1 40 1 0
#> 61 10.12 1 36 0 1
#> 59 10.16 1 NA 1 0
#> 154 12.63 1 20 1 0
#> 194 22.40 1 38 0 1
#> 190 20.81 1 42 1 0
#> 195 11.76 1 NA 1 0
#> 76 19.22 1 54 0 1
#> 8 18.43 1 32 0 0
#> 113 22.86 1 34 0 0
#> 106.1 16.67 1 49 1 0
#> 99.2 21.19 1 38 0 1
#> 10 10.53 1 34 0 0
#> 36 21.19 1 48 0 1
#> 32 20.90 1 37 1 0
#> 66 22.13 1 53 0 0
#> 10.1 10.53 1 34 0 0
#> 29 15.45 1 68 1 0
#> 50 10.02 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 52.1 10.42 1 52 0 1
#> 93 10.33 1 52 0 1
#> 10.2 10.53 1 34 0 0
#> 199 19.81 1 NA 0 1
#> 187.2 9.92 1 39 1 0
#> 76.1 19.22 1 54 0 1
#> 45 17.42 1 54 0 1
#> 187.3 9.92 1 39 1 0
#> 8.1 18.43 1 32 0 0
#> 197 21.60 1 69 1 0
#> 150 20.33 1 48 0 0
#> 39 15.59 1 37 0 1
#> 134 17.81 1 47 1 0
#> 140 12.68 1 59 1 0
#> 164 23.60 1 76 0 1
#> 68.1 20.62 1 44 0 0
#> 166 19.98 1 48 0 0
#> 181 16.46 1 45 0 1
#> 55 19.34 1 69 0 1
#> 79 16.23 1 54 1 0
#> 39.1 15.59 1 37 0 1
#> 40 18.00 1 28 1 0
#> 183 9.24 1 67 1 0
#> 76.2 19.22 1 54 0 1
#> 192 16.44 1 31 1 0
#> 8.2 18.43 1 32 0 0
#> 113.1 22.86 1 34 0 0
#> 111 17.45 1 47 0 1
#> 10.3 10.53 1 34 0 0
#> 113.2 22.86 1 34 0 0
#> 159 10.55 1 50 0 1
#> 179 18.63 1 42 0 0
#> 52.2 10.42 1 52 0 1
#> 114.1 13.68 1 NA 0 0
#> 192.1 16.44 1 31 1 0
#> 24 23.89 1 38 0 0
#> 37 12.52 1 57 1 0
#> 199.1 19.81 1 NA 0 1
#> 66.1 22.13 1 53 0 0
#> 111.1 17.45 1 47 0 1
#> 81 14.06 1 34 0 0
#> 195.1 11.76 1 NA 1 0
#> 32.1 20.90 1 37 1 0
#> 69 23.23 1 25 0 1
#> 91 5.33 1 61 0 1
#> 129 23.41 1 53 1 0
#> 6 15.64 1 39 0 0
#> 29.1 15.45 1 68 1 0
#> 90 20.94 1 50 0 1
#> 129.1 23.41 1 53 1 0
#> 69.1 23.23 1 25 0 1
#> 61.1 10.12 1 36 0 1
#> 37.1 12.52 1 57 1 0
#> 150.1 20.33 1 48 0 0
#> 43 12.10 1 61 0 1
#> 24.1 23.89 1 38 0 0
#> 169.1 22.41 1 46 0 0
#> 8.3 18.43 1 32 0 0
#> 56 12.21 1 60 0 0
#> 56.1 12.21 1 60 0 0
#> 149.1 8.37 1 33 1 0
#> 6.1 15.64 1 39 0 0
#> 134.1 17.81 1 47 1 0
#> 41.1 18.02 1 40 1 0
#> 189 10.51 1 NA 1 0
#> 96 14.54 1 33 0 1
#> 60 13.15 1 38 1 0
#> 10.4 10.53 1 34 0 0
#> 13 14.34 1 54 0 1
#> 110 17.56 1 65 0 1
#> 27 24.00 0 63 1 0
#> 132 24.00 0 55 0 0
#> 102 24.00 0 49 0 0
#> 185 24.00 0 44 1 0
#> 126 24.00 0 48 0 0
#> 62 24.00 0 71 0 0
#> 193 24.00 0 45 0 1
#> 72 24.00 0 40 0 1
#> 148 24.00 0 61 1 0
#> 62.1 24.00 0 71 0 0
#> 198 24.00 0 66 0 1
#> 143 24.00 0 51 0 0
#> 138 24.00 0 44 1 0
#> 147 24.00 0 76 1 0
#> 34 24.00 0 36 0 0
#> 83 24.00 0 6 0 0
#> 198.1 24.00 0 66 0 1
#> 196 24.00 0 19 0 0
#> 34.1 24.00 0 36 0 0
#> 22 24.00 0 52 1 0
#> 31 24.00 0 36 0 1
#> 112 24.00 0 61 0 0
#> 3 24.00 0 31 1 0
#> 193.1 24.00 0 45 0 1
#> 102.1 24.00 0 49 0 0
#> 1 24.00 0 23 1 0
#> 178 24.00 0 52 1 0
#> 160 24.00 0 31 1 0
#> 126.1 24.00 0 48 0 0
#> 7 24.00 0 37 1 0
#> 84 24.00 0 39 0 1
#> 21 24.00 0 47 0 0
#> 151 24.00 0 42 0 0
#> 95 24.00 0 68 0 1
#> 87 24.00 0 27 0 0
#> 95.1 24.00 0 68 0 1
#> 7.1 24.00 0 37 1 0
#> 116 24.00 0 58 0 1
#> 64 24.00 0 43 0 0
#> 163 24.00 0 66 0 0
#> 102.2 24.00 0 49 0 0
#> 176 24.00 0 43 0 1
#> 2 24.00 0 9 0 0
#> 83.1 24.00 0 6 0 0
#> 87.1 24.00 0 27 0 0
#> 122 24.00 0 66 0 0
#> 162 24.00 0 51 0 0
#> 33 24.00 0 53 0 0
#> 67 24.00 0 25 0 0
#> 193.2 24.00 0 45 0 1
#> 103 24.00 0 56 1 0
#> 126.2 24.00 0 48 0 0
#> 87.2 24.00 0 27 0 0
#> 72.1 24.00 0 40 0 1
#> 115 24.00 0 NA 1 0
#> 116.1 24.00 0 58 0 1
#> 33.1 24.00 0 53 0 0
#> 112.1 24.00 0 61 0 0
#> 3.1 24.00 0 31 1 0
#> 64.1 24.00 0 43 0 0
#> 119 24.00 0 17 0 0
#> 38 24.00 0 31 1 0
#> 182 24.00 0 35 0 0
#> 196.1 24.00 0 19 0 0
#> 178.1 24.00 0 52 1 0
#> 103.1 24.00 0 56 1 0
#> 142 24.00 0 53 0 0
#> 94 24.00 0 51 0 1
#> 161 24.00 0 45 0 0
#> 62.2 24.00 0 71 0 0
#> 182.1 24.00 0 35 0 0
#> 21.1 24.00 0 47 0 0
#> 174 24.00 0 49 1 0
#> 33.2 24.00 0 53 0 0
#> 135 24.00 0 58 1 0
#> 193.3 24.00 0 45 0 1
#> 17 24.00 0 38 0 1
#> 174.1 24.00 0 49 1 0
#> 109 24.00 0 48 0 0
#> 121 24.00 0 57 1 0
#> 172 24.00 0 41 0 0
#> 87.3 24.00 0 27 0 0
#> 19 24.00 0 57 0 1
#> 109.1 24.00 0 48 0 0
#> 109.2 24.00 0 48 0 0
#> 87.4 24.00 0 27 0 0
#> 17.1 24.00 0 38 0 1
#> 156 24.00 0 50 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.0288 NA NA NA
#> 2 age, Cure model -0.00650 NA NA NA
#> 3 grade_ii, Cure model 0.648 NA NA NA
#> 4 grade_iii, Cure model 0.901 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000968 NA NA NA
#> 2 grade_ii, Survival model 0.664 NA NA NA
#> 3 grade_iii, Survival model 0.423 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.028819 -0.006501 0.648164 0.900681
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 255.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.028819418 -0.006500673 0.648164130 0.900681490
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.0009680565 0.6644209865 0.4230261249
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.30834942 0.84836134 0.28255607 0.65374478 0.93625204 0.61164765
#> [7] 0.07049579 0.50269381 0.45460630 0.98746073 0.30834942 0.39400649
#> [13] 0.89599897 0.98746073 0.96843161 0.21663402 0.44445366 0.75493405
#> [19] 0.79177815 0.93625204 0.67800196 0.55856958 0.92292259 0.80627784
#> [25] 0.24339427 0.38376935 0.47439205 0.52169246 0.17755379 0.65374478
#> [31] 0.30834942 0.86216454 0.30834942 0.36300881 0.25672398 0.86216454
#> [37] 0.73996956 0.63696791 0.89599897 0.91617684 0.86216454 0.93625204
#> [43] 0.47439205 0.64538952 0.93625204 0.52169246 0.29575549 0.41417001
#> [49] 0.72467234 0.58569860 0.79906278 0.09715700 0.39400649 0.43428715
#> [55] 0.66992218 0.45460630 0.70139168 0.72467234 0.57670205 0.96198069
#> [61] 0.47439205 0.67800196 0.52169246 0.17755379 0.62021879 0.86216454
#> [67] 0.17755379 0.85527971 0.51219679 0.89599897 0.67800196 0.02688775
#> [73] 0.81343010 0.25672398 0.62021879 0.77713605 0.36300881 0.15025394
#> [79] 0.98112091 0.11986752 0.70918478 0.73996956 0.35181724 0.11986752
#> [85] 0.15025394 0.92292259 0.81343010 0.41417001 0.84138335 0.02688775
#> [91] 0.21663402 0.52169246 0.82741378 0.82741378 0.96843161 0.70918478
#> [97] 0.58569860 0.55856958 0.76237682 0.78449181 0.86216454 0.76977796
#> [103] 0.60300806 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 99 107 175 106 187 117 78 97 58 127 99.1 68 52
#> 21.19 11.18 21.91 16.67 9.92 17.46 23.88 19.14 19.34 3.53 21.19 20.62 10.42
#> 127.1 149 169 105 18 155 187.1 85 41 61 154 194 190
#> 3.53 8.37 22.41 19.75 15.21 13.08 9.92 16.44 18.02 10.12 12.63 22.40 20.81
#> 76 8 113 106.1 99.2 10 36 32 66 10.1 29 30 52.1
#> 19.22 18.43 22.86 16.67 21.19 10.53 21.19 20.90 22.13 10.53 15.45 17.43 10.42
#> 93 10.2 187.2 76.1 45 187.3 8.1 197 150 39 134 140 164
#> 10.33 10.53 9.92 19.22 17.42 9.92 18.43 21.60 20.33 15.59 17.81 12.68 23.60
#> 68.1 166 181 55 79 39.1 40 183 76.2 192 8.2 113.1 111
#> 20.62 19.98 16.46 19.34 16.23 15.59 18.00 9.24 19.22 16.44 18.43 22.86 17.45
#> 10.3 113.2 159 179 52.2 192.1 24 37 66.1 111.1 81 32.1 69
#> 10.53 22.86 10.55 18.63 10.42 16.44 23.89 12.52 22.13 17.45 14.06 20.90 23.23
#> 91 129 6 29.1 90 129.1 69.1 61.1 37.1 150.1 43 24.1 169.1
#> 5.33 23.41 15.64 15.45 20.94 23.41 23.23 10.12 12.52 20.33 12.10 23.89 22.41
#> 8.3 56 56.1 149.1 6.1 134.1 41.1 96 60 10.4 13 110 27
#> 18.43 12.21 12.21 8.37 15.64 17.81 18.02 14.54 13.15 10.53 14.34 17.56 24.00
#> 132 102 185 126 62 193 72 148 62.1 198 143 138 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 83 198.1 196 34.1 22 31 112 3 193.1 102.1 1 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160 126.1 7 84 21 151 95 87 95.1 7.1 116 64 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102.2 176 2 83.1 87.1 122 162 33 67 193.2 103 126.2 87.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.1 116.1 33.1 112.1 3.1 64.1 119 38 182 196.1 178.1 103.1 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 161 62.2 182.1 21.1 174 33.2 135 193.3 17 174.1 109 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172 87.3 19 109.1 109.2 87.4 17.1 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[78]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00363329 0.33594250 0.31842594
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.18509798 0.01712181 0.56444360
#> grade_iii, Cure model
#> 0.99315772
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 164 23.60 1 76 0 1
#> 188 16.16 1 46 0 1
#> 129 23.41 1 53 1 0
#> 190 20.81 1 42 1 0
#> 127 3.53 1 62 0 1
#> 97 19.14 1 65 0 1
#> 108 18.29 1 39 0 1
#> 45 17.42 1 54 0 1
#> 168 23.72 1 70 0 0
#> 51 18.23 1 83 0 1
#> 16 8.71 1 71 0 1
#> 58 19.34 1 39 0 0
#> 155 13.08 1 26 0 0
#> 4 17.64 1 NA 0 1
#> 77 7.27 1 67 0 1
#> 180 14.82 1 37 0 0
#> 177 12.53 1 75 0 0
#> 43 12.10 1 61 0 1
#> 169 22.41 1 46 0 0
#> 127.1 3.53 1 62 0 1
#> 57 14.46 1 45 0 1
#> 181 16.46 1 45 0 1
#> 175 21.91 1 43 0 0
#> 100 16.07 1 60 0 0
#> 110 17.56 1 65 0 1
#> 130 16.47 1 53 0 1
#> 16.1 8.71 1 71 0 1
#> 175.1 21.91 1 43 0 0
#> 32 20.90 1 37 1 0
#> 81 14.06 1 34 0 0
#> 88 18.37 1 47 0 0
#> 89 11.44 1 NA 0 0
#> 180.1 14.82 1 37 0 0
#> 86 23.81 1 58 0 1
#> 134 17.81 1 47 1 0
#> 39 15.59 1 37 0 1
#> 66 22.13 1 53 0 0
#> 51.1 18.23 1 83 0 1
#> 101 9.97 1 10 0 1
#> 32.1 20.90 1 37 1 0
#> 18 15.21 1 49 1 0
#> 45.1 17.42 1 54 0 1
#> 45.2 17.42 1 54 0 1
#> 60 13.15 1 38 1 0
#> 155.1 13.08 1 26 0 0
#> 26 15.77 1 49 0 1
#> 37 12.52 1 57 1 0
#> 181.1 16.46 1 45 0 1
#> 90 20.94 1 50 0 1
#> 5 16.43 1 51 0 1
#> 37.1 12.52 1 57 1 0
#> 134.1 17.81 1 47 1 0
#> 92 22.92 1 47 0 1
#> 133 14.65 1 57 0 0
#> 111 17.45 1 47 0 1
#> 26.1 15.77 1 49 0 1
#> 194 22.40 1 38 0 1
#> 190.1 20.81 1 42 1 0
#> 10 10.53 1 34 0 0
#> 190.2 20.81 1 42 1 0
#> 149 8.37 1 33 1 0
#> 111.1 17.45 1 47 0 1
#> 86.1 23.81 1 58 0 1
#> 133.1 14.65 1 57 0 0
#> 117 17.46 1 26 0 1
#> 130.1 16.47 1 53 0 1
#> 49 12.19 1 48 1 0
#> 177.1 12.53 1 75 0 0
#> 106 16.67 1 49 1 0
#> 188.1 16.16 1 46 0 1
#> 79 16.23 1 54 1 0
#> 114 13.68 1 NA 0 0
#> 96 14.54 1 33 0 1
#> 16.2 8.71 1 71 0 1
#> 125 15.65 1 67 1 0
#> 117.1 17.46 1 26 0 1
#> 114.1 13.68 1 NA 0 0
#> 194.1 22.40 1 38 0 1
#> 127.2 3.53 1 62 0 1
#> 140 12.68 1 59 1 0
#> 36 21.19 1 48 0 1
#> 41 18.02 1 40 1 0
#> 195 11.76 1 NA 1 0
#> 140.1 12.68 1 59 1 0
#> 124 9.73 1 NA 1 0
#> 190.3 20.81 1 42 1 0
#> 130.2 16.47 1 53 0 1
#> 136 21.83 1 43 0 1
#> 24 23.89 1 38 0 0
#> 158 20.14 1 74 1 0
#> 50 10.02 1 NA 1 0
#> 159 10.55 1 50 0 1
#> 59 10.16 1 NA 1 0
#> 41.1 18.02 1 40 1 0
#> 59.1 10.16 1 NA 1 0
#> 24.1 23.89 1 38 0 0
#> 134.2 17.81 1 47 1 0
#> 195.1 11.76 1 NA 1 0
#> 23 16.92 1 61 0 0
#> 40 18.00 1 28 1 0
#> 127.3 3.53 1 62 0 1
#> 55 19.34 1 69 0 1
#> 197 21.60 1 69 1 0
#> 25 6.32 1 34 1 0
#> 57.1 14.46 1 45 0 1
#> 129.1 23.41 1 53 1 0
#> 18.1 15.21 1 49 1 0
#> 125.1 15.65 1 67 1 0
#> 164.1 23.60 1 76 0 1
#> 85 16.44 1 36 0 0
#> 81.1 14.06 1 34 0 0
#> 66.1 22.13 1 53 0 0
#> 147 24.00 0 76 1 0
#> 21 24.00 0 47 0 0
#> 72 24.00 0 40 0 1
#> 112 24.00 0 61 0 0
#> 118 24.00 0 44 1 0
#> 198 24.00 0 66 0 1
#> 48 24.00 0 31 1 0
#> 200 24.00 0 64 0 0
#> 102 24.00 0 49 0 0
#> 73 24.00 0 NA 0 1
#> 71 24.00 0 51 0 0
#> 67 24.00 0 25 0 0
#> 103 24.00 0 56 1 0
#> 143 24.00 0 51 0 0
#> 191 24.00 0 60 0 1
#> 143.1 24.00 0 51 0 0
#> 120 24.00 0 68 0 1
#> 122 24.00 0 66 0 0
#> 9 24.00 0 31 1 0
#> 65 24.00 0 57 1 0
#> 122.1 24.00 0 66 0 0
#> 147.1 24.00 0 76 1 0
#> 46 24.00 0 71 0 0
#> 112.1 24.00 0 61 0 0
#> 71.1 24.00 0 51 0 0
#> 1 24.00 0 23 1 0
#> 115 24.00 0 NA 1 0
#> 72.1 24.00 0 40 0 1
#> 2 24.00 0 9 0 0
#> 148 24.00 0 61 1 0
#> 11 24.00 0 42 0 1
#> 21.1 24.00 0 47 0 0
#> 102.1 24.00 0 49 0 0
#> 144 24.00 0 28 0 1
#> 73.1 24.00 0 NA 0 1
#> 80 24.00 0 41 0 0
#> 21.2 24.00 0 47 0 0
#> 9.1 24.00 0 31 1 0
#> 144.1 24.00 0 28 0 1
#> 17 24.00 0 38 0 1
#> 80.1 24.00 0 41 0 0
#> 144.2 24.00 0 28 0 1
#> 34 24.00 0 36 0 0
#> 47 24.00 0 38 0 1
#> 34.1 24.00 0 36 0 0
#> 116 24.00 0 58 0 1
#> 102.2 24.00 0 49 0 0
#> 152 24.00 0 36 0 1
#> 27 24.00 0 63 1 0
#> 142 24.00 0 53 0 0
#> 31 24.00 0 36 0 1
#> 17.1 24.00 0 38 0 1
#> 144.3 24.00 0 28 0 1
#> 173 24.00 0 19 0 1
#> 122.2 24.00 0 66 0 0
#> 182 24.00 0 35 0 0
#> 109 24.00 0 48 0 0
#> 98 24.00 0 34 1 0
#> 95 24.00 0 68 0 1
#> 44 24.00 0 56 0 0
#> 161 24.00 0 45 0 0
#> 72.2 24.00 0 40 0 1
#> 48.1 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 148.1 24.00 0 61 1 0
#> 198.1 24.00 0 66 0 1
#> 146 24.00 0 63 1 0
#> 73.2 24.00 0 NA 0 1
#> 72.3 24.00 0 40 0 1
#> 72.4 24.00 0 40 0 1
#> 44.1 24.00 0 56 0 0
#> 75 24.00 0 21 1 0
#> 191.1 24.00 0 60 0 1
#> 172 24.00 0 41 0 0
#> 143.2 24.00 0 51 0 0
#> 9.2 24.00 0 31 1 0
#> 103.1 24.00 0 56 1 0
#> 163 24.00 0 66 0 0
#> 138 24.00 0 44 1 0
#> 122.3 24.00 0 66 0 0
#> 160 24.00 0 31 1 0
#> 126 24.00 0 48 0 0
#> 141 24.00 0 44 1 0
#> 186 24.00 0 45 1 0
#> 156 24.00 0 50 1 0
#> 31.1 24.00 0 36 0 1
#> 191.2 24.00 0 60 0 1
#> 9.3 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.19 NA NA NA
#> 2 age, Cure model 0.0171 NA NA NA
#> 3 grade_ii, Cure model 0.564 NA NA NA
#> 4 grade_iii, Cure model 0.993 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00363 NA NA NA
#> 2 grade_ii, Survival model 0.336 NA NA NA
#> 3 grade_iii, Survival model 0.318 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.18510 0.01712 0.56444 0.99316
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.1
#> Residual Deviance: 245.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.18509798 0.01712181 0.56444360 0.99315772
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00363329 0.33594250 0.31842594
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.06497583 0.60648723 0.08707620 0.25906397 0.96429235 0.32798521
#> [7] 0.34833307 0.48478092 0.05262884 0.35847367 0.90984315 0.30794725
#> [13] 0.79057990 0.94609804 0.69870866 0.82721659 0.87313769 0.11942738
#> [19] 0.96429235 0.74471882 0.55971447 0.17274405 0.62497433 0.43687262
#> [25] 0.53186249 0.90984315 0.17274405 0.23827863 0.76302026 0.33813510
#> [31] 0.69870866 0.03179861 0.40814464 0.67118721 0.15143315 0.35847367
#> [37] 0.90068761 0.23827863 0.68043100 0.48478092 0.48478092 0.78137287
#> [43] 0.79057990 0.63431453 0.84560513 0.55971447 0.22743349 0.58774111
#> [49] 0.84560513 0.40814464 0.10837633 0.71704668 0.46577637 0.63431453
#> [55] 0.13063874 0.25906397 0.89150165 0.25906397 0.93698380 0.46577637
#> [61] 0.03179861 0.71704668 0.44664775 0.53186249 0.86393887 0.82721659
#> [67] 0.52234362 0.60648723 0.59712520 0.73547288 0.90984315 0.65277609
#> [73] 0.44664775 0.13063874 0.96429235 0.80892505 0.21651215 0.37844936
#> [79] 0.80892505 0.25906397 0.53186249 0.19444515 0.01008826 0.29778086
#> [85] 0.88232667 0.37844936 0.01008826 0.40814464 0.51279498 0.39820635
#> [91] 0.96429235 0.30794725 0.20550493 0.95520544 0.74471882 0.08707620
#> [97] 0.68043100 0.65277609 0.06497583 0.57833563 0.76302026 0.15143315
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 164 188 129 190 127 97 108 45 168 51 16 58 155
#> 23.60 16.16 23.41 20.81 3.53 19.14 18.29 17.42 23.72 18.23 8.71 19.34 13.08
#> 77 180 177 43 169 127.1 57 181 175 100 110 130 16.1
#> 7.27 14.82 12.53 12.10 22.41 3.53 14.46 16.46 21.91 16.07 17.56 16.47 8.71
#> 175.1 32 81 88 180.1 86 134 39 66 51.1 101 32.1 18
#> 21.91 20.90 14.06 18.37 14.82 23.81 17.81 15.59 22.13 18.23 9.97 20.90 15.21
#> 45.1 45.2 60 155.1 26 37 181.1 90 5 37.1 134.1 92 133
#> 17.42 17.42 13.15 13.08 15.77 12.52 16.46 20.94 16.43 12.52 17.81 22.92 14.65
#> 111 26.1 194 190.1 10 190.2 149 111.1 86.1 133.1 117 130.1 49
#> 17.45 15.77 22.40 20.81 10.53 20.81 8.37 17.45 23.81 14.65 17.46 16.47 12.19
#> 177.1 106 188.1 79 96 16.2 125 117.1 194.1 127.2 140 36 41
#> 12.53 16.67 16.16 16.23 14.54 8.71 15.65 17.46 22.40 3.53 12.68 21.19 18.02
#> 140.1 190.3 130.2 136 24 158 159 41.1 24.1 134.2 23 40 127.3
#> 12.68 20.81 16.47 21.83 23.89 20.14 10.55 18.02 23.89 17.81 16.92 18.00 3.53
#> 55 197 25 57.1 129.1 18.1 125.1 164.1 85 81.1 66.1 147 21
#> 19.34 21.60 6.32 14.46 23.41 15.21 15.65 23.60 16.44 14.06 22.13 24.00 24.00
#> 72 112 118 198 48 200 102 71 67 103 143 191 143.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 122 9 65 122.1 147.1 46 112.1 71.1 1 72.1 2 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11 21.1 102.1 144 80 21.2 9.1 144.1 17 80.1 144.2 34 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34.1 116 102.2 152 27 142 31 17.1 144.3 173 122.2 182 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 95 44 161 72.2 48.1 7 148.1 198.1 146 72.3 72.4 44.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 191.1 172 143.2 9.2 103.1 163 138 122.3 160 126 141 186
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 31.1 191.2 9.3
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[79]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.007827306 0.547063925 0.289323837
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.0285187 0.0192563 -0.0769238
#> grade_iii, Cure model
#> 0.9903847
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 99 21.19 1 38 0 1
#> 194 22.40 1 38 0 1
#> 43 12.10 1 61 0 1
#> 171 16.57 1 41 0 1
#> 81 14.06 1 34 0 0
#> 68 20.62 1 44 0 0
#> 129 23.41 1 53 1 0
#> 92 22.92 1 47 0 1
#> 76 19.22 1 54 0 1
#> 124 9.73 1 NA 1 0
#> 41 18.02 1 40 1 0
#> 166 19.98 1 48 0 0
#> 177 12.53 1 75 0 0
#> 195 11.76 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 169 22.41 1 46 0 0
#> 15 22.68 1 48 0 0
#> 197 21.60 1 69 1 0
#> 101 9.97 1 10 0 1
#> 49 12.19 1 48 1 0
#> 188 16.16 1 46 0 1
#> 189 10.51 1 NA 1 0
#> 76.1 19.22 1 54 0 1
#> 129.1 23.41 1 53 1 0
#> 188.1 16.16 1 46 0 1
#> 171.1 16.57 1 41 0 1
#> 61 10.12 1 36 0 1
#> 145 10.07 1 65 1 0
#> 86 23.81 1 58 0 1
#> 199 19.81 1 NA 0 1
#> 189.1 10.51 1 NA 1 0
#> 101.1 9.97 1 10 0 1
#> 59 10.16 1 NA 1 0
#> 45 17.42 1 54 0 1
#> 114 13.68 1 NA 0 0
#> 70 7.38 1 30 1 0
#> 26 15.77 1 49 0 1
#> 100 16.07 1 60 0 0
#> 4 17.64 1 NA 0 1
#> 106 16.67 1 49 1 0
#> 23 16.92 1 61 0 0
#> 56 12.21 1 60 0 0
#> 41.1 18.02 1 40 1 0
#> 140 12.68 1 59 1 0
#> 154 12.63 1 20 1 0
#> 69 23.23 1 25 0 1
#> 111 17.45 1 47 0 1
#> 50 10.02 1 NA 1 0
#> 96 14.54 1 33 0 1
#> 183 9.24 1 67 1 0
#> 168 23.72 1 70 0 0
#> 133 14.65 1 57 0 0
#> 69.1 23.23 1 25 0 1
#> 60 13.15 1 38 1 0
#> 45.1 17.42 1 54 0 1
#> 26.1 15.77 1 49 0 1
#> 129.2 23.41 1 53 1 0
#> 89 11.44 1 NA 0 0
#> 194.1 22.40 1 38 0 1
#> 125 15.65 1 67 1 0
#> 18 15.21 1 49 1 0
#> 37 12.52 1 57 1 0
#> 175 21.91 1 43 0 0
#> 76.2 19.22 1 54 0 1
#> 63 22.77 1 31 1 0
#> 129.3 23.41 1 53 1 0
#> 197.1 21.60 1 69 1 0
#> 59.1 10.16 1 NA 1 0
#> 166.1 19.98 1 48 0 0
#> 117 17.46 1 26 0 1
#> 81.1 14.06 1 34 0 0
#> 78 23.88 1 43 0 0
#> 129.4 23.41 1 53 1 0
#> 90 20.94 1 50 0 1
#> 86.1 23.81 1 58 0 1
#> 189.2 10.51 1 NA 1 0
#> 26.2 15.77 1 49 0 1
#> 6 15.64 1 39 0 0
#> 45.2 17.42 1 54 0 1
#> 60.1 13.15 1 38 1 0
#> 164 23.60 1 76 0 1
#> 175.1 21.91 1 43 0 0
#> 78.1 23.88 1 43 0 0
#> 5 16.43 1 51 0 1
#> 79 16.23 1 54 1 0
#> 13 14.34 1 54 0 1
#> 169.1 22.41 1 46 0 0
#> 86.2 23.81 1 58 0 1
#> 58 19.34 1 39 0 0
#> 42 12.43 1 49 0 1
#> 125.1 15.65 1 67 1 0
#> 133.1 14.65 1 57 0 0
#> 61.1 10.12 1 36 0 1
#> 128 20.35 1 35 0 1
#> 106.1 16.67 1 49 1 0
#> 51 18.23 1 83 0 1
#> 114.1 13.68 1 NA 0 0
#> 24 23.89 1 38 0 0
#> 149 8.37 1 33 1 0
#> 171.2 16.57 1 41 0 1
#> 111.1 17.45 1 47 0 1
#> 93 10.33 1 52 0 1
#> 68.1 20.62 1 44 0 0
#> 166.2 19.98 1 48 0 0
#> 113 22.86 1 34 0 0
#> 86.3 23.81 1 58 0 1
#> 194.2 22.40 1 38 0 1
#> 177.1 12.53 1 75 0 0
#> 68.2 20.62 1 44 0 0
#> 66 22.13 1 53 0 0
#> 158 20.14 1 74 1 0
#> 183.1 9.24 1 67 1 0
#> 1 24.00 0 23 1 0
#> 109 24.00 0 48 0 0
#> 146 24.00 0 63 1 0
#> 84 24.00 0 39 0 1
#> 176 24.00 0 43 0 1
#> 3 24.00 0 31 1 0
#> 94 24.00 0 51 0 1
#> 98 24.00 0 34 1 0
#> 191 24.00 0 60 0 1
#> 35 24.00 0 51 0 0
#> 115 24.00 0 NA 1 0
#> 65 24.00 0 57 1 0
#> 165 24.00 0 47 0 0
#> 1.1 24.00 0 23 1 0
#> 191.1 24.00 0 60 0 1
#> 71 24.00 0 51 0 0
#> 94.1 24.00 0 51 0 1
#> 109.1 24.00 0 48 0 0
#> 146.1 24.00 0 63 1 0
#> 172 24.00 0 41 0 0
#> 2 24.00 0 9 0 0
#> 31 24.00 0 36 0 1
#> 119 24.00 0 17 0 0
#> 148 24.00 0 61 1 0
#> 122 24.00 0 66 0 0
#> 142 24.00 0 53 0 0
#> 148.1 24.00 0 61 1 0
#> 98.1 24.00 0 34 1 0
#> 20 24.00 0 46 1 0
#> 7 24.00 0 37 1 0
#> 160 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 182 24.00 0 35 0 0
#> 135 24.00 0 58 1 0
#> 44 24.00 0 56 0 0
#> 162 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 196 24.00 0 19 0 0
#> 191.2 24.00 0 60 0 1
#> 132 24.00 0 55 0 0
#> 119.1 24.00 0 17 0 0
#> 20.1 24.00 0 46 1 0
#> 19 24.00 0 57 0 1
#> 38 24.00 0 31 1 0
#> 1.2 24.00 0 23 1 0
#> 176.1 24.00 0 43 0 1
#> 54 24.00 0 53 1 0
#> 160.1 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 11 24.00 0 42 0 1
#> 126.1 24.00 0 48 0 0
#> 172.1 24.00 0 41 0 0
#> 94.2 24.00 0 51 0 1
#> 182.1 24.00 0 35 0 0
#> 53 24.00 0 32 0 1
#> 54.1 24.00 0 53 1 0
#> 34 24.00 0 36 0 0
#> 34.1 24.00 0 36 0 0
#> 44.1 24.00 0 56 0 0
#> 118 24.00 0 44 1 0
#> 102 24.00 0 49 0 0
#> 102.1 24.00 0 49 0 0
#> 33 24.00 0 53 0 0
#> 7.1 24.00 0 37 1 0
#> 20.2 24.00 0 46 1 0
#> 156.1 24.00 0 50 1 0
#> 1.3 24.00 0 23 1 0
#> 46 24.00 0 71 0 0
#> 131 24.00 0 66 0 0
#> 186 24.00 0 45 1 0
#> 74 24.00 0 43 0 1
#> 115.1 24.00 0 NA 1 0
#> 11.1 24.00 0 42 0 1
#> 161 24.00 0 45 0 0
#> 185 24.00 0 44 1 0
#> 172.2 24.00 0 41 0 0
#> 152 24.00 0 36 0 1
#> 120 24.00 0 68 0 1
#> 151 24.00 0 42 0 0
#> 115.2 24.00 0 NA 1 0
#> 138 24.00 0 44 1 0
#> 34.2 24.00 0 36 0 0
#> 135.1 24.00 0 58 1 0
#> 178 24.00 0 52 1 0
#> 191.3 24.00 0 60 0 1
#> 20.3 24.00 0 46 1 0
#> 131.1 24.00 0 66 0 0
#> 174 24.00 0 49 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.03 NA NA NA
#> 2 age, Cure model 0.0193 NA NA NA
#> 3 grade_ii, Cure model -0.0769 NA NA NA
#> 4 grade_iii, Cure model 0.990 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00783 NA NA NA
#> 2 grade_ii, Survival model 0.547 NA NA NA
#> 3 grade_iii, Survival model 0.289 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.02852 0.01926 -0.07692 0.99038
#>
#> Degrees of Freedom: 183 Total (i.e. Null); 180 Residual
#> Null Deviance: 254
#> Residual Deviance: 241.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.0285187 0.0192563 -0.0769238 0.9903847
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.007827306 0.547063925 0.289323837
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.269636007 0.194287347 0.880101663 0.547011391 0.749550890 0.289290814
#> [7] 0.081600163 0.138991682 0.379642686 0.431774008 0.338901366 0.814627379
#> [13] 0.410477696 0.175719504 0.166480727 0.250377349 0.934886454 0.869150835
#> [19] 0.599631293 0.379642686 0.081600163 0.599631293 0.547011391 0.902065186
#> [25] 0.923905886 0.029216091 0.934886454 0.484020428 0.989172451 0.631482648
#> [31] 0.620758574 0.525958703 0.515247979 0.858174160 0.431774008 0.792957549
#> [37] 0.803827348 0.121402695 0.463142004 0.727769578 0.956599501 0.059957938
#> [43] 0.706160890 0.121402695 0.771340769 0.484020428 0.631482648 0.081600163
#> [49] 0.194287347 0.663254992 0.695392149 0.836338199 0.231109047 0.379642686
#> [55] 0.157399870 0.081600163 0.250377349 0.338901366 0.452618748 0.749550890
#> [61] 0.011629519 0.081600163 0.279446632 0.029216091 0.631482648 0.684593704
#> [67] 0.484020428 0.771340769 0.070559472 0.231109047 0.011629519 0.578340784
#> [73] 0.588998777 0.738650210 0.175719504 0.029216091 0.369182346 0.847249854
#> [79] 0.663254992 0.706160890 0.902065186 0.318676140 0.525958703 0.421085113
#> [85] 0.003025699 0.978301293 0.547011391 0.463142004 0.891075910 0.289290814
#> [91] 0.338901366 0.148128894 0.029216091 0.194287347 0.814627379 0.289290814
#> [97] 0.221499639 0.328783820 0.956599501 0.000000000 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 99 194 43 171 81 68 129 92 76 41 166 177 8
#> 21.19 22.40 12.10 16.57 14.06 20.62 23.41 22.92 19.22 18.02 19.98 12.53 18.43
#> 169 15 197 101 49 188 76.1 129.1 188.1 171.1 61 145 86
#> 22.41 22.68 21.60 9.97 12.19 16.16 19.22 23.41 16.16 16.57 10.12 10.07 23.81
#> 101.1 45 70 26 100 106 23 56 41.1 140 154 69 111
#> 9.97 17.42 7.38 15.77 16.07 16.67 16.92 12.21 18.02 12.68 12.63 23.23 17.45
#> 96 183 168 133 69.1 60 45.1 26.1 129.2 194.1 125 18 37
#> 14.54 9.24 23.72 14.65 23.23 13.15 17.42 15.77 23.41 22.40 15.65 15.21 12.52
#> 175 76.2 63 129.3 197.1 166.1 117 81.1 78 129.4 90 86.1 26.2
#> 21.91 19.22 22.77 23.41 21.60 19.98 17.46 14.06 23.88 23.41 20.94 23.81 15.77
#> 6 45.2 60.1 164 175.1 78.1 5 79 13 169.1 86.2 58 42
#> 15.64 17.42 13.15 23.60 21.91 23.88 16.43 16.23 14.34 22.41 23.81 19.34 12.43
#> 125.1 133.1 61.1 128 106.1 51 24 149 171.2 111.1 93 68.1 166.2
#> 15.65 14.65 10.12 20.35 16.67 18.23 23.89 8.37 16.57 17.45 10.33 20.62 19.98
#> 113 86.3 194.2 177.1 68.2 66 158 183.1 1 109 146 84 176
#> 22.86 23.81 22.40 12.53 20.62 22.13 20.14 9.24 24.00 24.00 24.00 24.00 24.00
#> 3 94 98 191 35 65 165 1.1 191.1 71 94.1 109.1 146.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172 2 31 119 148 122 142 148.1 98.1 20 7 160 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 135 44 162 126 196 191.2 132 119.1 20.1 19 38 1.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176.1 54 160.1 9 11 126.1 172.1 94.2 182.1 53 54.1 34 34.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44.1 118 102 102.1 33 7.1 20.2 156.1 1.3 46 131 186 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11.1 161 185 172.2 152 120 151 138 34.2 135.1 178 191.3 20.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.1 174
#> 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[80]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.009015534 0.617750175 0.311597039
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.62683678 0.02474092 0.57640353
#> grade_iii, Cure model
#> 1.36769618
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 145 10.07 1 65 1 0
#> 26 15.77 1 49 0 1
#> 195 11.76 1 NA 1 0
#> 70 7.38 1 30 1 0
#> 66 22.13 1 53 0 0
#> 187 9.92 1 39 1 0
#> 129 23.41 1 53 1 0
#> 157 15.10 1 47 0 0
#> 16 8.71 1 71 0 1
#> 77 7.27 1 67 0 1
#> 124 9.73 1 NA 1 0
#> 171 16.57 1 41 0 1
#> 49 12.19 1 48 1 0
#> 43 12.10 1 61 0 1
#> 180 14.82 1 37 0 0
#> 50 10.02 1 NA 1 0
#> 133 14.65 1 57 0 0
#> 90 20.94 1 50 0 1
#> 39 15.59 1 37 0 1
#> 70.1 7.38 1 30 1 0
#> 166 19.98 1 48 0 0
#> 150 20.33 1 48 0 0
#> 90.1 20.94 1 50 0 1
#> 171.1 16.57 1 41 0 1
#> 81 14.06 1 34 0 0
#> 32 20.90 1 37 1 0
#> 158 20.14 1 74 1 0
#> 68 20.62 1 44 0 0
#> 166.1 19.98 1 48 0 0
#> 195.1 11.76 1 NA 1 0
#> 129.1 23.41 1 53 1 0
#> 89 11.44 1 NA 0 0
#> 30 17.43 1 78 0 0
#> 96 14.54 1 33 0 1
#> 180.1 14.82 1 37 0 0
#> 42 12.43 1 49 0 1
#> 108 18.29 1 39 0 1
#> 97 19.14 1 65 0 1
#> 86 23.81 1 58 0 1
#> 14 12.89 1 21 0 0
#> 101 9.97 1 10 0 1
#> 97.1 19.14 1 65 0 1
#> 26.1 15.77 1 49 0 1
#> 192 16.44 1 31 1 0
#> 42.1 12.43 1 49 0 1
#> 155 13.08 1 26 0 0
#> 51 18.23 1 83 0 1
#> 164 23.60 1 76 0 1
#> 90.2 20.94 1 50 0 1
#> 108.1 18.29 1 39 0 1
#> 91 5.33 1 61 0 1
#> 49.1 12.19 1 48 1 0
#> 187.1 9.92 1 39 1 0
#> 86.1 23.81 1 58 0 1
#> 49.2 12.19 1 48 1 0
#> 157.1 15.10 1 47 0 0
#> 195.2 11.76 1 NA 1 0
#> 175 21.91 1 43 0 0
#> 52 10.42 1 52 0 1
#> 189 10.51 1 NA 1 0
#> 194 22.40 1 38 0 1
#> 197 21.60 1 69 1 0
#> 50.1 10.02 1 NA 1 0
#> 180.2 14.82 1 37 0 0
#> 153 21.33 1 55 1 0
#> 110 17.56 1 65 0 1
#> 77.1 7.27 1 67 0 1
#> 136 21.83 1 43 0 1
#> 188 16.16 1 46 0 1
#> 114 13.68 1 NA 0 0
#> 180.3 14.82 1 37 0 0
#> 36 21.19 1 48 0 1
#> 188.1 16.16 1 46 0 1
#> 194.1 22.40 1 38 0 1
#> 166.2 19.98 1 48 0 0
#> 149 8.37 1 33 1 0
#> 145.1 10.07 1 65 1 0
#> 4 17.64 1 NA 0 1
#> 113 22.86 1 34 0 0
#> 130 16.47 1 53 0 1
#> 29 15.45 1 68 1 0
#> 133.1 14.65 1 57 0 0
#> 43.1 12.10 1 61 0 1
#> 52.1 10.42 1 52 0 1
#> 26.2 15.77 1 49 0 1
#> 111 17.45 1 47 0 1
#> 96.1 14.54 1 33 0 1
#> 155.1 13.08 1 26 0 0
#> 127 3.53 1 62 0 1
#> 180.4 14.82 1 37 0 0
#> 106 16.67 1 49 1 0
#> 91.1 5.33 1 61 0 1
#> 93 10.33 1 52 0 1
#> 90.3 20.94 1 50 0 1
#> 18 15.21 1 49 1 0
#> 192.1 16.44 1 31 1 0
#> 140 12.68 1 59 1 0
#> 100 16.07 1 60 0 0
#> 52.2 10.42 1 52 0 1
#> 79 16.23 1 54 1 0
#> 97.2 19.14 1 65 0 1
#> 187.2 9.92 1 39 1 0
#> 114.1 13.68 1 NA 0 0
#> 110.1 17.56 1 65 0 1
#> 24 23.89 1 38 0 0
#> 125 15.65 1 67 1 0
#> 6 15.64 1 39 0 0
#> 183 9.24 1 67 1 0
#> 24.1 23.89 1 38 0 0
#> 50.2 10.02 1 NA 1 0
#> 66.1 22.13 1 53 0 0
#> 37 12.52 1 57 1 0
#> 185 24.00 0 44 1 0
#> 137 24.00 0 45 1 0
#> 132 24.00 0 55 0 0
#> 185.1 24.00 0 44 1 0
#> 64 24.00 0 43 0 0
#> 132.1 24.00 0 55 0 0
#> 122 24.00 0 66 0 0
#> 118 24.00 0 44 1 0
#> 62 24.00 0 71 0 0
#> 47 24.00 0 38 0 1
#> 132.2 24.00 0 55 0 0
#> 172 24.00 0 41 0 0
#> 176 24.00 0 43 0 1
#> 47.1 24.00 0 38 0 1
#> 182 24.00 0 35 0 0
#> 142 24.00 0 53 0 0
#> 112 24.00 0 61 0 0
#> 9 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 3 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 28 24.00 0 67 1 0
#> 182.1 24.00 0 35 0 0
#> 33 24.00 0 53 0 0
#> 104.1 24.00 0 50 1 0
#> 94 24.00 0 51 0 1
#> 165 24.00 0 47 0 0
#> 74 24.00 0 43 0 1
#> 34 24.00 0 36 0 0
#> 19 24.00 0 57 0 1
#> 7 24.00 0 37 1 0
#> 176.1 24.00 0 43 0 1
#> 196 24.00 0 19 0 0
#> 98 24.00 0 34 1 0
#> 118.1 24.00 0 44 1 0
#> 176.2 24.00 0 43 0 1
#> 9.1 24.00 0 31 1 0
#> 34.1 24.00 0 36 0 0
#> 173 24.00 0 19 0 1
#> 172.1 24.00 0 41 0 0
#> 141 24.00 0 44 1 0
#> 186 24.00 0 45 1 0
#> 121 24.00 0 57 1 0
#> 163 24.00 0 66 0 0
#> 87 24.00 0 27 0 0
#> 132.3 24.00 0 55 0 0
#> 71 24.00 0 51 0 0
#> 143 24.00 0 51 0 0
#> 161 24.00 0 45 0 0
#> 84 24.00 0 39 0 1
#> 3.1 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 73 24.00 0 NA 0 1
#> 87.1 24.00 0 27 0 0
#> 47.2 24.00 0 38 0 1
#> 193 24.00 0 45 0 1
#> 141.1 24.00 0 44 1 0
#> 142.1 24.00 0 53 0 0
#> 53 24.00 0 32 0 1
#> 122.1 24.00 0 66 0 0
#> 71.1 24.00 0 51 0 0
#> 67 24.00 0 25 0 0
#> 46 24.00 0 71 0 0
#> 182.2 24.00 0 35 0 0
#> 196.1 24.00 0 19 0 0
#> 132.4 24.00 0 55 0 0
#> 87.2 24.00 0 27 0 0
#> 2 24.00 0 9 0 0
#> 27 24.00 0 63 1 0
#> 191 24.00 0 60 0 1
#> 119 24.00 0 17 0 0
#> 9.2 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 35 24.00 0 51 0 0
#> 64.1 24.00 0 43 0 0
#> 186.1 24.00 0 45 1 0
#> 87.3 24.00 0 27 0 0
#> 19.1 24.00 0 57 0 1
#> 142.2 24.00 0 53 0 0
#> 178 24.00 0 52 1 0
#> 162 24.00 0 51 0 0
#> 67.1 24.00 0 25 0 0
#> 12 24.00 0 63 0 0
#> 102 24.00 0 49 0 0
#> 53.1 24.00 0 32 0 1
#> 122.2 24.00 0 66 0 0
#> 143.1 24.00 0 51 0 0
#> 84.1 24.00 0 39 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.63 NA NA NA
#> 2 age, Cure model 0.0247 NA NA NA
#> 3 grade_ii, Cure model 0.576 NA NA NA
#> 4 grade_iii, Cure model 1.37 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00902 NA NA NA
#> 2 grade_ii, Survival model 0.618 NA NA NA
#> 3 grade_iii, Survival model 0.312 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.62684 0.02474 0.57640 1.36770
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258.3
#> Residual Deviance: 237.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.62683678 0.02474092 0.57640353 1.36769618
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.009015534 0.617750175 0.311597039
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.824220078 0.436121814 0.923492365 0.074239469 0.857664084 0.036518419
#> [7] 0.519114386 0.901398311 0.945190658 0.344002743 0.725024439 0.757749246
#> [13] 0.540112286 0.592491225 0.135738291 0.487651386 0.923492365 0.206135099
#> [19] 0.187539723 0.135738291 0.344002743 0.636188864 0.169433765 0.196826787
#> [25] 0.178411505 0.206135099 0.036518419 0.323116030 0.614345514 0.540112286
#> [31] 0.702835491 0.262878567 0.234092713 0.014460017 0.669359281 0.846491049
#> [37] 0.234092713 0.436121814 0.375065500 0.702835491 0.647256534 0.282495485
#> [43] 0.027924857 0.135738291 0.262878567 0.967016010 0.725024439 0.857664084
#> [49] 0.014460017 0.725024439 0.519114386 0.090780715 0.779861952 0.058996458
#> [55] 0.108765050 0.540112286 0.117790820 0.292606884 0.945190658 0.099742937
#> [61] 0.405502618 0.540112286 0.126728188 0.405502618 0.058996458 0.206135099
#> [67] 0.912470578 0.824220078 0.050887950 0.364580963 0.498153589 0.592491225
#> [73] 0.757749246 0.779861952 0.436121814 0.312809973 0.614345514 0.647256534
#> [79] 0.988946348 0.540112286 0.333590826 0.967016010 0.812998510 0.135738291
#> [85] 0.508654759 0.375065500 0.680535521 0.425763609 0.779861952 0.395293042
#> [91] 0.234092713 0.857664084 0.292606884 0.003535292 0.466724848 0.477154106
#> [97] 0.890363996 0.003535292 0.074239469 0.691695340 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 145 26 70 66 187 129 157 16 77 171 49 43 180
#> 10.07 15.77 7.38 22.13 9.92 23.41 15.10 8.71 7.27 16.57 12.19 12.10 14.82
#> 133 90 39 70.1 166 150 90.1 171.1 81 32 158 68 166.1
#> 14.65 20.94 15.59 7.38 19.98 20.33 20.94 16.57 14.06 20.90 20.14 20.62 19.98
#> 129.1 30 96 180.1 42 108 97 86 14 101 97.1 26.1 192
#> 23.41 17.43 14.54 14.82 12.43 18.29 19.14 23.81 12.89 9.97 19.14 15.77 16.44
#> 42.1 155 51 164 90.2 108.1 91 49.1 187.1 86.1 49.2 157.1 175
#> 12.43 13.08 18.23 23.60 20.94 18.29 5.33 12.19 9.92 23.81 12.19 15.10 21.91
#> 52 194 197 180.2 153 110 77.1 136 188 180.3 36 188.1 194.1
#> 10.42 22.40 21.60 14.82 21.33 17.56 7.27 21.83 16.16 14.82 21.19 16.16 22.40
#> 166.2 149 145.1 113 130 29 133.1 43.1 52.1 26.2 111 96.1 155.1
#> 19.98 8.37 10.07 22.86 16.47 15.45 14.65 12.10 10.42 15.77 17.45 14.54 13.08
#> 127 180.4 106 91.1 93 90.3 18 192.1 140 100 52.2 79 97.2
#> 3.53 14.82 16.67 5.33 10.33 20.94 15.21 16.44 12.68 16.07 10.42 16.23 19.14
#> 187.2 110.1 24 125 6 183 24.1 66.1 37 185 137 132 185.1
#> 9.92 17.56 23.89 15.65 15.64 9.24 23.89 22.13 12.52 24.00 24.00 24.00 24.00
#> 64 132.1 122 118 62 47 132.2 172 176 47.1 182 142 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 156 3 104 28 182.1 33 104.1 94 165 74 34 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 176.1 196 98 118.1 176.2 9.1 34.1 173 172.1 141 186 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163 87 132.3 71 143 161 84 3.1 72 87.1 47.2 193 141.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142.1 53 122.1 71.1 67 46 182.2 196.1 132.4 87.2 2 27 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119 9.2 138 35 64.1 186.1 87.3 19.1 142.2 178 162 67.1 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 53.1 122.2 143.1 84.1
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[81]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004736228 0.687855344 0.191941776
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.309592235 0.008187698 -0.212990176
#> grade_iii, Cure model
#> 0.587828218
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 139 21.49 1 63 1 0
#> 188 16.16 1 46 0 1
#> 32 20.90 1 37 1 0
#> 77 7.27 1 67 0 1
#> 134 17.81 1 47 1 0
#> 187 9.92 1 39 1 0
#> 29 15.45 1 68 1 0
#> 179 18.63 1 42 0 0
#> 68 20.62 1 44 0 0
#> 90 20.94 1 50 0 1
#> 57 14.46 1 45 0 1
#> 171 16.57 1 41 0 1
#> 194 22.40 1 38 0 1
#> 167 15.55 1 56 1 0
#> 179.1 18.63 1 42 0 0
#> 40 18.00 1 28 1 0
#> 183 9.24 1 67 1 0
#> 88 18.37 1 47 0 0
#> 195 11.76 1 NA 1 0
#> 169 22.41 1 46 0 0
#> 59 10.16 1 NA 1 0
#> 59.1 10.16 1 NA 1 0
#> 15 22.68 1 48 0 0
#> 99 21.19 1 38 0 1
#> 13 14.34 1 54 0 1
#> 59.2 10.16 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 69 23.23 1 25 0 1
#> 4 17.64 1 NA 0 1
#> 179.2 18.63 1 42 0 0
#> 15.1 22.68 1 48 0 0
#> 57.1 14.46 1 45 0 1
#> 30 17.43 1 78 0 0
#> 41 18.02 1 40 1 0
#> 164 23.60 1 76 0 1
#> 56 12.21 1 60 0 0
#> 24 23.89 1 38 0 0
#> 49 12.19 1 48 1 0
#> 93 10.33 1 52 0 1
#> 197 21.60 1 69 1 0
#> 106 16.67 1 49 1 0
#> 164.1 23.60 1 76 0 1
#> 154 12.63 1 20 1 0
#> 68.1 20.62 1 44 0 0
#> 93.1 10.33 1 52 0 1
#> 42 12.43 1 49 0 1
#> 23 16.92 1 61 0 0
#> 57.2 14.46 1 45 0 1
#> 177 12.53 1 75 0 0
#> 130 16.47 1 53 0 1
#> 166 19.98 1 48 0 0
#> 184 17.77 1 38 0 0
#> 105 19.75 1 60 0 0
#> 127 3.53 1 62 0 1
#> 18 15.21 1 49 1 0
#> 41.1 18.02 1 40 1 0
#> 49.1 12.19 1 48 1 0
#> 123 13.00 1 44 1 0
#> 40.1 18.00 1 28 1 0
#> 57.3 14.46 1 45 0 1
#> 197.1 21.60 1 69 1 0
#> 159 10.55 1 50 0 1
#> 70 7.38 1 30 1 0
#> 68.2 20.62 1 44 0 0
#> 110 17.56 1 65 0 1
#> 45 17.42 1 54 0 1
#> 136 21.83 1 43 0 1
#> 92 22.92 1 47 0 1
#> 114 13.68 1 NA 0 0
#> 117 17.46 1 26 0 1
#> 133 14.65 1 57 0 0
#> 184.1 17.77 1 38 0 0
#> 194.1 22.40 1 38 0 1
#> 110.1 17.56 1 65 0 1
#> 49.2 12.19 1 48 1 0
#> 145 10.07 1 65 1 0
#> 8.1 18.43 1 32 0 0
#> 42.1 12.43 1 49 0 1
#> 136.1 21.83 1 43 0 1
#> 30.1 17.43 1 78 0 0
#> 85 16.44 1 36 0 0
#> 97 19.14 1 65 0 1
#> 179.3 18.63 1 42 0 0
#> 49.3 12.19 1 48 1 0
#> 154.1 12.63 1 20 1 0
#> 183.1 9.24 1 67 1 0
#> 23.1 16.92 1 61 0 0
#> 43 12.10 1 61 0 1
#> 14 12.89 1 21 0 0
#> 154.2 12.63 1 20 1 0
#> 36 21.19 1 48 0 1
#> 168 23.72 1 70 0 0
#> 139.1 21.49 1 63 1 0
#> 79 16.23 1 54 1 0
#> 57.4 14.46 1 45 0 1
#> 199 19.81 1 NA 0 1
#> 10 10.53 1 34 0 0
#> 85.1 16.44 1 36 0 0
#> 124 9.73 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 169.1 22.41 1 46 0 0
#> 140 12.68 1 59 1 0
#> 45.1 17.42 1 54 0 1
#> 105.1 19.75 1 60 0 0
#> 30.2 17.43 1 78 0 0
#> 70.1 7.38 1 30 1 0
#> 177.1 12.53 1 75 0 0
#> 91 5.33 1 61 0 1
#> 197.2 21.60 1 69 1 0
#> 166.1 19.98 1 48 0 0
#> 23.2 16.92 1 61 0 0
#> 51 18.23 1 83 0 1
#> 31 24.00 0 36 0 1
#> 156 24.00 0 50 1 0
#> 11 24.00 0 42 0 1
#> 163 24.00 0 66 0 0
#> 131 24.00 0 66 0 0
#> 83 24.00 0 6 0 0
#> 71 24.00 0 51 0 0
#> 109 24.00 0 48 0 0
#> 20 24.00 0 46 1 0
#> 83.1 24.00 0 6 0 0
#> 132 24.00 0 55 0 0
#> 65 24.00 0 57 1 0
#> 178 24.00 0 52 1 0
#> 34 24.00 0 36 0 0
#> 135 24.00 0 58 1 0
#> 102 24.00 0 49 0 0
#> 165 24.00 0 47 0 0
#> 172 24.00 0 41 0 0
#> 64 24.00 0 43 0 0
#> 148 24.00 0 61 1 0
#> 198 24.00 0 66 0 1
#> 95 24.00 0 68 0 1
#> 84 24.00 0 39 0 1
#> 28 24.00 0 67 1 0
#> 102.1 24.00 0 49 0 0
#> 54 24.00 0 53 1 0
#> 132.1 24.00 0 55 0 0
#> 131.1 24.00 0 66 0 0
#> 185 24.00 0 44 1 0
#> 84.1 24.00 0 39 0 1
#> 138 24.00 0 44 1 0
#> 115 24.00 0 NA 1 0
#> 121 24.00 0 57 1 0
#> 104 24.00 0 50 1 0
#> 3 24.00 0 31 1 0
#> 94 24.00 0 51 0 1
#> 53 24.00 0 32 0 1
#> 98 24.00 0 34 1 0
#> 44 24.00 0 56 0 0
#> 160 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 148.1 24.00 0 61 1 0
#> 54.1 24.00 0 53 1 0
#> 191 24.00 0 60 0 1
#> 34.1 24.00 0 36 0 0
#> 196 24.00 0 19 0 0
#> 31.1 24.00 0 36 0 1
#> 109.1 24.00 0 48 0 0
#> 191.1 24.00 0 60 0 1
#> 116 24.00 0 58 0 1
#> 178.1 24.00 0 52 1 0
#> 141 24.00 0 44 1 0
#> 65.1 24.00 0 57 1 0
#> 64.1 24.00 0 43 0 0
#> 116.1 24.00 0 58 0 1
#> 21 24.00 0 47 0 0
#> 126 24.00 0 48 0 0
#> 142 24.00 0 53 0 0
#> 83.2 24.00 0 6 0 0
#> 103 24.00 0 56 1 0
#> 74 24.00 0 43 0 1
#> 27 24.00 0 63 1 0
#> 118.1 24.00 0 44 1 0
#> 95.1 24.00 0 68 0 1
#> 84.2 24.00 0 39 0 1
#> 156.1 24.00 0 50 1 0
#> 3.1 24.00 0 31 1 0
#> 116.2 24.00 0 58 0 1
#> 12 24.00 0 63 0 0
#> 174 24.00 0 49 1 0
#> 3.2 24.00 0 31 1 0
#> 28.1 24.00 0 67 1 0
#> 48 24.00 0 31 1 0
#> 54.2 24.00 0 53 1 0
#> 132.2 24.00 0 55 0 0
#> 142.1 24.00 0 53 0 0
#> 84.3 24.00 0 39 0 1
#> 135.1 24.00 0 58 1 0
#> 27.1 24.00 0 63 1 0
#> 20.1 24.00 0 46 1 0
#> 83.3 24.00 0 6 0 0
#> 163.1 24.00 0 66 0 0
#> 148.2 24.00 0 61 1 0
#> 143 24.00 0 51 0 0
#> 126.1 24.00 0 48 0 0
#> 71.1 24.00 0 51 0 0
#> 162 24.00 0 51 0 0
#> 131.2 24.00 0 66 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.310 NA NA NA
#> 2 age, Cure model 0.00819 NA NA NA
#> 3 grade_ii, Cure model -0.213 NA NA NA
#> 4 grade_iii, Cure model 0.588 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00474 NA NA NA
#> 2 grade_ii, Survival model 0.688 NA NA NA
#> 3 grade_iii, Survival model 0.192 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.309592 0.008188 -0.212990 0.587828
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 257.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.309592235 0.008187698 -0.212990176 0.587828218
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004736228 0.687855344 0.191941776
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.177745225 0.622329840 0.225373567 0.973528464 0.429480564 0.929218251
#> [7] 0.651634696 0.311280017 0.234820878 0.215653511 0.680500290 0.573427976
#> [13] 0.104737813 0.641906026 0.311280017 0.410467354 0.938223082 0.370203753
#> [19] 0.082759223 0.061890916 0.196688282 0.727311918 0.350075078 0.040644294
#> [25] 0.311280017 0.061890916 0.680500290 0.486443001 0.390777363 0.021939689
#> [31] 0.829762336 0.003480718 0.839072301 0.902038657 0.148672771 0.563635944
#> [37] 0.021939689 0.765528438 0.234820878 0.902038657 0.811297823 0.534479905
#> [43] 0.680500290 0.792849845 0.583220386 0.262647569 0.438968962 0.281823733
#> [49] 0.991168646 0.661299642 0.390777363 0.839072301 0.736932889 0.410467354
#> [55] 0.680500290 0.148672771 0.883862614 0.955994073 0.234820878 0.457873925
#> [61] 0.515128974 0.126678337 0.051230460 0.476864806 0.670883713 0.438968962
#> [67] 0.104737813 0.457873925 0.839072301 0.920155994 0.350075078 0.811297823
#> [73] 0.126678337 0.486443001 0.593022241 0.301328584 0.311280017 0.839072301
#> [79] 0.765528438 0.938223082 0.534479905 0.874785565 0.746477206 0.765528438
#> [85] 0.196688282 0.011523955 0.177745225 0.612564420 0.680500290 0.892943756
#> [91] 0.593022241 0.632099186 0.082759223 0.756033091 0.515128974 0.281823733
#> [97] 0.486443001 0.955994073 0.792849845 0.982344896 0.148672771 0.262647569
#> [103] 0.534479905 0.380465210 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 139 188 32 77 134 187 29 179 68 90 57 171 194
#> 21.49 16.16 20.90 7.27 17.81 9.92 15.45 18.63 20.62 20.94 14.46 16.57 22.40
#> 167 179.1 40 183 88 169 15 99 13 8 69 179.2 15.1
#> 15.55 18.63 18.00 9.24 18.37 22.41 22.68 21.19 14.34 18.43 23.23 18.63 22.68
#> 57.1 30 41 164 56 24 49 93 197 106 164.1 154 68.1
#> 14.46 17.43 18.02 23.60 12.21 23.89 12.19 10.33 21.60 16.67 23.60 12.63 20.62
#> 93.1 42 23 57.2 177 130 166 184 105 127 18 41.1 49.1
#> 10.33 12.43 16.92 14.46 12.53 16.47 19.98 17.77 19.75 3.53 15.21 18.02 12.19
#> 123 40.1 57.3 197.1 159 70 68.2 110 45 136 92 117 133
#> 13.00 18.00 14.46 21.60 10.55 7.38 20.62 17.56 17.42 21.83 22.92 17.46 14.65
#> 184.1 194.1 110.1 49.2 145 8.1 42.1 136.1 30.1 85 97 179.3 49.3
#> 17.77 22.40 17.56 12.19 10.07 18.43 12.43 21.83 17.43 16.44 19.14 18.63 12.19
#> 154.1 183.1 23.1 43 14 154.2 36 168 139.1 79 57.4 10 85.1
#> 12.63 9.24 16.92 12.10 12.89 12.63 21.19 23.72 21.49 16.23 14.46 10.53 16.44
#> 100 169.1 140 45.1 105.1 30.2 70.1 177.1 91 197.2 166.1 23.2 51
#> 16.07 22.41 12.68 17.42 19.75 17.43 7.38 12.53 5.33 21.60 19.98 16.92 18.23
#> 31 156 11 163 131 83 71 109 20 83.1 132 65 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 135 102 165 172 64 148 198 95 84 28 102.1 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.1 131.1 185 84.1 138 121 104 3 94 53 98 44 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 148.1 54.1 191 34.1 196 31.1 109.1 191.1 116 178.1 141 65.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64.1 116.1 21 126 142 83.2 103 74 27 118.1 95.1 84.2 156.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.1 116.2 12 174 3.2 28.1 48 54.2 132.2 142.1 84.3 135.1 27.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20.1 83.3 163.1 148.2 143 126.1 71.1 162 131.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[82]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001880218 0.265437499 0.241402154
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.369766337 0.006382256 -0.161601005
#> grade_iii, Cure model
#> 0.985392412
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 29 15.45 1 68 1 0
#> 30 17.43 1 78 0 0
#> 8 18.43 1 32 0 0
#> 97 19.14 1 65 0 1
#> 99 21.19 1 38 0 1
#> 149 8.37 1 33 1 0
#> 114 13.68 1 NA 0 0
#> 81 14.06 1 34 0 0
#> 183 9.24 1 67 1 0
#> 88 18.37 1 47 0 0
#> 10 10.53 1 34 0 0
#> 5 16.43 1 51 0 1
#> 45 17.42 1 54 0 1
#> 183.1 9.24 1 67 1 0
#> 66 22.13 1 53 0 0
#> 55 19.34 1 69 0 1
#> 129 23.41 1 53 1 0
#> 150 20.33 1 48 0 0
#> 68 20.62 1 44 0 0
#> 51 18.23 1 83 0 1
#> 55.1 19.34 1 69 0 1
#> 129.1 23.41 1 53 1 0
#> 136 21.83 1 43 0 1
#> 40 18.00 1 28 1 0
#> 184 17.77 1 38 0 0
#> 55.2 19.34 1 69 0 1
#> 92 22.92 1 47 0 1
#> 128 20.35 1 35 0 1
#> 39 15.59 1 37 0 1
#> 114.1 13.68 1 NA 0 0
#> 61 10.12 1 36 0 1
#> 127 3.53 1 62 0 1
#> 86 23.81 1 58 0 1
#> 43 12.10 1 61 0 1
#> 113 22.86 1 34 0 0
#> 123 13.00 1 44 1 0
#> 26 15.77 1 49 0 1
#> 40.1 18.00 1 28 1 0
#> 175 21.91 1 43 0 0
#> 101 9.97 1 10 0 1
#> 16 8.71 1 71 0 1
#> 58 19.34 1 39 0 0
#> 117 17.46 1 26 0 1
#> 97.1 19.14 1 65 0 1
#> 180 14.82 1 37 0 0
#> 124 9.73 1 NA 1 0
#> 123.1 13.00 1 44 1 0
#> 113.1 22.86 1 34 0 0
#> 10.1 10.53 1 34 0 0
#> 88.1 18.37 1 47 0 0
#> 197 21.60 1 69 1 0
#> 117.1 17.46 1 26 0 1
#> 166 19.98 1 48 0 0
#> 85 16.44 1 36 0 0
#> 125 15.65 1 67 1 0
#> 133 14.65 1 57 0 0
#> 134 17.81 1 47 1 0
#> 4 17.64 1 NA 0 1
#> 197.1 21.60 1 69 1 0
#> 107 11.18 1 54 1 0
#> 79 16.23 1 54 1 0
#> 125.1 15.65 1 67 1 0
#> 183.2 9.24 1 67 1 0
#> 187 9.92 1 39 1 0
#> 23 16.92 1 61 0 0
#> 61.1 10.12 1 36 0 1
#> 6 15.64 1 39 0 0
#> 159 10.55 1 50 0 1
#> 51.1 18.23 1 83 0 1
#> 68.1 20.62 1 44 0 0
#> 110 17.56 1 65 0 1
#> 129.2 23.41 1 53 1 0
#> 99.1 21.19 1 38 0 1
#> 50 10.02 1 NA 1 0
#> 179 18.63 1 42 0 0
#> 5.1 16.43 1 51 0 1
#> 77 7.27 1 67 0 1
#> 14 12.89 1 21 0 0
#> 24 23.89 1 38 0 0
#> 13 14.34 1 54 0 1
#> 26.1 15.77 1 49 0 1
#> 111 17.45 1 47 0 1
#> 195 11.76 1 NA 1 0
#> 181 16.46 1 45 0 1
#> 195.1 11.76 1 NA 1 0
#> 39.1 15.59 1 37 0 1
#> 10.2 10.53 1 34 0 0
#> 36 21.19 1 48 0 1
#> 16.1 8.71 1 71 0 1
#> 169 22.41 1 46 0 0
#> 194 22.40 1 38 0 1
#> 91 5.33 1 61 0 1
#> 154 12.63 1 20 1 0
#> 177 12.53 1 75 0 0
#> 90 20.94 1 50 0 1
#> 190 20.81 1 42 1 0
#> 16.2 8.71 1 71 0 1
#> 134.1 17.81 1 47 1 0
#> 50.1 10.02 1 NA 1 0
#> 36.1 21.19 1 48 0 1
#> 169.1 22.41 1 46 0 0
#> 37 12.52 1 57 1 0
#> 134.2 17.81 1 47 1 0
#> 93 10.33 1 52 0 1
#> 97.2 19.14 1 65 0 1
#> 99.2 21.19 1 38 0 1
#> 100 16.07 1 60 0 0
#> 8.1 18.43 1 32 0 0
#> 41 18.02 1 40 1 0
#> 51.2 18.23 1 83 0 1
#> 123.2 13.00 1 44 1 0
#> 55.3 19.34 1 69 0 1
#> 80 24.00 0 41 0 0
#> 116 24.00 0 58 0 1
#> 196 24.00 0 19 0 0
#> 7 24.00 0 37 1 0
#> 137 24.00 0 45 1 0
#> 135 24.00 0 58 1 0
#> 163 24.00 0 66 0 0
#> 20 24.00 0 46 1 0
#> 112 24.00 0 61 0 0
#> 118 24.00 0 44 1 0
#> 160 24.00 0 31 1 0
#> 131 24.00 0 66 0 0
#> 122 24.00 0 66 0 0
#> 193 24.00 0 45 0 1
#> 64 24.00 0 43 0 0
#> 185 24.00 0 44 1 0
#> 173 24.00 0 19 0 1
#> 38 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 122.1 24.00 0 66 0 0
#> 53 24.00 0 32 0 1
#> 46 24.00 0 71 0 0
#> 163.1 24.00 0 66 0 0
#> 48 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#> 144 24.00 0 28 0 1
#> 22 24.00 0 52 1 0
#> 20.1 24.00 0 46 1 0
#> 1 24.00 0 23 1 0
#> 35 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 109 24.00 0 48 0 0
#> 185.1 24.00 0 44 1 0
#> 3 24.00 0 31 1 0
#> 144.1 24.00 0 28 0 1
#> 121 24.00 0 57 1 0
#> 147 24.00 0 76 1 0
#> 44.1 24.00 0 56 0 0
#> 73 24.00 0 NA 0 1
#> 115 24.00 0 NA 1 0
#> 33 24.00 0 53 0 0
#> 191 24.00 0 60 0 1
#> 152 24.00 0 36 0 1
#> 131.1 24.00 0 66 0 0
#> 172.1 24.00 0 41 0 0
#> 94 24.00 0 51 0 1
#> 182 24.00 0 35 0 0
#> 84 24.00 0 39 0 1
#> 126 24.00 0 48 0 0
#> 137.1 24.00 0 45 1 0
#> 160.1 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 75 24.00 0 21 1 0
#> 87 24.00 0 27 0 0
#> 148 24.00 0 61 1 0
#> 143 24.00 0 51 0 0
#> 116.1 24.00 0 58 0 1
#> 143.1 24.00 0 51 0 0
#> 132 24.00 0 55 0 0
#> 142 24.00 0 53 0 0
#> 94.1 24.00 0 51 0 1
#> 44.2 24.00 0 56 0 0
#> 75.1 24.00 0 21 1 0
#> 62 24.00 0 71 0 0
#> 122.2 24.00 0 66 0 0
#> 104 24.00 0 50 1 0
#> 75.2 24.00 0 21 1 0
#> 71 24.00 0 51 0 0
#> 73.1 24.00 0 NA 0 1
#> 132.1 24.00 0 55 0 0
#> 104.1 24.00 0 50 1 0
#> 135.1 24.00 0 58 1 0
#> 22.1 24.00 0 52 1 0
#> 151 24.00 0 42 0 0
#> 198 24.00 0 66 0 1
#> 118.1 24.00 0 44 1 0
#> 95.1 24.00 0 68 0 1
#> 33.1 24.00 0 53 0 0
#> 82 24.00 0 34 0 0
#> 146 24.00 0 63 1 0
#> 48.1 24.00 0 31 1 0
#> 118.2 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 178 24.00 0 52 1 0
#> 19 24.00 0 57 0 1
#> 156 24.00 0 50 1 0
#> 104.2 24.00 0 50 1 0
#> 173.1 24.00 0 19 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.370 NA NA NA
#> 2 age, Cure model 0.00638 NA NA NA
#> 3 grade_ii, Cure model -0.162 NA NA NA
#> 4 grade_iii, Cure model 0.985 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00188 NA NA NA
#> 2 grade_ii, Survival model 0.265 NA NA NA
#> 3 grade_iii, Survival model 0.241 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.369766 0.006382 -0.161601 0.985392
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.1
#> Residual Deviance: 248.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.369766337 0.006382256 -0.161601005 0.985392412
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001880218 0.265437499 0.241402154
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.74908215 0.61743506 0.45803648 0.42089391 0.25111970 0.97079813
#> [7] 0.78090780 0.92675399 0.47663843 0.86625304 0.65966381 0.62594523
#> [13] 0.92675399 0.18901170 0.37440318 0.07042645 0.35377366 0.32279458
#> [19] 0.49517364 0.37440318 0.07042645 0.21501801 0.53101896 0.57449507
#> [25] 0.37440318 0.10936916 0.34341657 0.73313774 0.89660163 0.99273440
#> [31] 0.04716115 0.84319346 0.12354256 0.78882767 0.69271163 0.53101896
#> [37] 0.20204993 0.91167748 0.94889227 0.37440318 0.59187578 0.42089391
#> [43] 0.75705613 0.78882767 0.12354256 0.86625304 0.47663843 0.22769567
#> [49] 0.59187578 0.36410221 0.65126457 0.70897280 0.76502407 0.54870525
#> [55] 0.22769567 0.85090969 0.67618763 0.70897280 0.92675399 0.91922820
#> [61] 0.63440834 0.89660163 0.72505726 0.85859503 0.49517364 0.32279458
#> [67] 0.58321382 0.07042645 0.25111970 0.44861518 0.65966381 0.97813416
#> [73] 0.81206109 0.01858818 0.77298262 0.69271163 0.60890632 0.64285775
#> [79] 0.73313774 0.86625304 0.25111970 0.94889227 0.14991067 0.17587894
#> [85] 0.98544585 0.81987759 0.82766779 0.30156640 0.31225463 0.94889227
#> [91] 0.54870525 0.25111970 0.14991067 0.83544691 0.54870525 0.88898517
#> [97] 0.42089391 0.25111970 0.68445559 0.45803648 0.52198735 0.49517364
#> [103] 0.78882767 0.37440318 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 29 30 8 97 99 149 81 183 88 10 5 45 183.1
#> 15.45 17.43 18.43 19.14 21.19 8.37 14.06 9.24 18.37 10.53 16.43 17.42 9.24
#> 66 55 129 150 68 51 55.1 129.1 136 40 184 55.2 92
#> 22.13 19.34 23.41 20.33 20.62 18.23 19.34 23.41 21.83 18.00 17.77 19.34 22.92
#> 128 39 61 127 86 43 113 123 26 40.1 175 101 16
#> 20.35 15.59 10.12 3.53 23.81 12.10 22.86 13.00 15.77 18.00 21.91 9.97 8.71
#> 58 117 97.1 180 123.1 113.1 10.1 88.1 197 117.1 166 85 125
#> 19.34 17.46 19.14 14.82 13.00 22.86 10.53 18.37 21.60 17.46 19.98 16.44 15.65
#> 133 134 197.1 107 79 125.1 183.2 187 23 61.1 6 159 51.1
#> 14.65 17.81 21.60 11.18 16.23 15.65 9.24 9.92 16.92 10.12 15.64 10.55 18.23
#> 68.1 110 129.2 99.1 179 5.1 77 14 24 13 26.1 111 181
#> 20.62 17.56 23.41 21.19 18.63 16.43 7.27 12.89 23.89 14.34 15.77 17.45 16.46
#> 39.1 10.2 36 16.1 169 194 91 154 177 90 190 16.2 134.1
#> 15.59 10.53 21.19 8.71 22.41 22.40 5.33 12.63 12.53 20.94 20.81 8.71 17.81
#> 36.1 169.1 37 134.2 93 97.2 99.2 100 8.1 41 51.2 123.2 55.3
#> 21.19 22.41 12.52 17.81 10.33 19.14 21.19 16.07 18.43 18.02 18.23 13.00 19.34
#> 80 116 196 7 137 135 163 20 112 118 160 131 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 64 185 173 38 172 122.1 53 46 163.1 48 95 144
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 20.1 1 35 44 109 185.1 3 144.1 121 147 44.1 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191 152 131.1 172.1 94 182 84 126 137.1 160.1 31 75 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 143 116.1 143.1 132 142 94.1 44.2 75.1 62 122.2 104 75.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 132.1 104.1 135.1 22.1 151 198 118.1 95.1 33.1 82 146 48.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118.2 27 178 19 156 104.2 173.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[83]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01186965 0.35522198 -0.05790933
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.88470239 0.01788684 0.26480711
#> grade_iii, Cure model
#> 0.36824527
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 164 23.60 1 76 0 1
#> 69 23.23 1 25 0 1
#> 56 12.21 1 60 0 0
#> 59 10.16 1 NA 1 0
#> 18 15.21 1 49 1 0
#> 113 22.86 1 34 0 0
#> 168 23.72 1 70 0 0
#> 155 13.08 1 26 0 0
#> 107 11.18 1 54 1 0
#> 86 23.81 1 58 0 1
#> 42 12.43 1 49 0 1
#> 108 18.29 1 39 0 1
#> 177 12.53 1 75 0 0
#> 110 17.56 1 65 0 1
#> 106 16.67 1 49 1 0
#> 105 19.75 1 60 0 0
#> 197 21.60 1 69 1 0
#> 170 19.54 1 43 0 1
#> 157 15.10 1 47 0 0
#> 183 9.24 1 67 1 0
#> 108.1 18.29 1 39 0 1
#> 40 18.00 1 28 1 0
#> 195 11.76 1 NA 1 0
#> 127 3.53 1 62 0 1
#> 100 16.07 1 60 0 0
#> 188 16.16 1 46 0 1
#> 36 21.19 1 48 0 1
#> 89 11.44 1 NA 0 0
#> 25 6.32 1 34 1 0
#> 70 7.38 1 30 1 0
#> 199 19.81 1 NA 0 1
#> 29 15.45 1 68 1 0
#> 51 18.23 1 83 0 1
#> 106.1 16.67 1 49 1 0
#> 190 20.81 1 42 1 0
#> 6 15.64 1 39 0 0
#> 24 23.89 1 38 0 0
#> 127.1 3.53 1 62 0 1
#> 61 10.12 1 36 0 1
#> 188.1 16.16 1 46 0 1
#> 157.1 15.10 1 47 0 0
#> 188.2 16.16 1 46 0 1
#> 41 18.02 1 40 1 0
#> 100.1 16.07 1 60 0 0
#> 158 20.14 1 74 1 0
#> 93 10.33 1 52 0 1
#> 123 13.00 1 44 1 0
#> 92 22.92 1 47 0 1
#> 68 20.62 1 44 0 0
#> 93.1 10.33 1 52 0 1
#> 113.1 22.86 1 34 0 0
#> 77 7.27 1 67 0 1
#> 108.2 18.29 1 39 0 1
#> 106.2 16.67 1 49 1 0
#> 177.1 12.53 1 75 0 0
#> 50 10.02 1 NA 1 0
#> 123.1 13.00 1 44 1 0
#> 140 12.68 1 59 1 0
#> 25.1 6.32 1 34 1 0
#> 18.1 15.21 1 49 1 0
#> 10 10.53 1 34 0 0
#> 26 15.77 1 49 0 1
#> 199.1 19.81 1 NA 0 1
#> 97 19.14 1 65 0 1
#> 145 10.07 1 65 1 0
#> 180 14.82 1 37 0 0
#> 192 16.44 1 31 1 0
#> 36.1 21.19 1 48 0 1
#> 197.1 21.60 1 69 1 0
#> 101 9.97 1 10 0 1
#> 76 19.22 1 54 0 1
#> 81 14.06 1 34 0 0
#> 92.1 22.92 1 47 0 1
#> 36.2 21.19 1 48 0 1
#> 139 21.49 1 63 1 0
#> 51.1 18.23 1 83 0 1
#> 32 20.90 1 37 1 0
#> 6.1 15.64 1 39 0 0
#> 36.3 21.19 1 48 0 1
#> 36.4 21.19 1 48 0 1
#> 61.1 10.12 1 36 0 1
#> 187 9.92 1 39 1 0
#> 32.1 20.90 1 37 1 0
#> 55 19.34 1 69 0 1
#> 10.1 10.53 1 34 0 0
#> 70.1 7.38 1 30 1 0
#> 85 16.44 1 36 0 0
#> 88 18.37 1 47 0 0
#> 26.1 15.77 1 49 0 1
#> 154 12.63 1 20 1 0
#> 108.3 18.29 1 39 0 1
#> 92.2 22.92 1 47 0 1
#> 42.1 12.43 1 49 0 1
#> 123.2 13.00 1 44 1 0
#> 180.1 14.82 1 37 0 0
#> 124 9.73 1 NA 1 0
#> 89.1 11.44 1 NA 0 0
#> 197.2 21.60 1 69 1 0
#> 42.2 12.43 1 49 0 1
#> 125 15.65 1 67 1 0
#> 79 16.23 1 54 1 0
#> 18.2 15.21 1 49 1 0
#> 77.1 7.27 1 67 0 1
#> 164.1 23.60 1 76 0 1
#> 190.1 20.81 1 42 1 0
#> 90 20.94 1 50 0 1
#> 56.1 12.21 1 60 0 0
#> 13 14.34 1 54 0 1
#> 105.1 19.75 1 60 0 0
#> 106.3 16.67 1 49 1 0
#> 101.1 9.97 1 10 0 1
#> 124.1 9.73 1 NA 1 0
#> 7 24.00 0 37 1 0
#> 173 24.00 0 19 0 1
#> 34 24.00 0 36 0 0
#> 102 24.00 0 49 0 0
#> 35 24.00 0 51 0 0
#> 182 24.00 0 35 0 0
#> 7.1 24.00 0 37 1 0
#> 27 24.00 0 63 1 0
#> 74 24.00 0 43 0 1
#> 103 24.00 0 56 1 0
#> 135 24.00 0 58 1 0
#> 64 24.00 0 43 0 0
#> 17 24.00 0 38 0 1
#> 11 24.00 0 42 0 1
#> 146 24.00 0 63 1 0
#> 48 24.00 0 31 1 0
#> 196 24.00 0 19 0 0
#> 174 24.00 0 49 1 0
#> 146.1 24.00 0 63 1 0
#> 120 24.00 0 68 0 1
#> 72 24.00 0 40 0 1
#> 191 24.00 0 60 0 1
#> 118 24.00 0 44 1 0
#> 74.1 24.00 0 43 0 1
#> 200 24.00 0 64 0 0
#> 21 24.00 0 47 0 0
#> 131 24.00 0 66 0 0
#> 17.1 24.00 0 38 0 1
#> 182.1 24.00 0 35 0 0
#> 119 24.00 0 17 0 0
#> 35.1 24.00 0 51 0 0
#> 9 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 115 24.00 0 NA 1 0
#> 80 24.00 0 41 0 0
#> 47 24.00 0 38 0 1
#> 2 24.00 0 9 0 0
#> 146.2 24.00 0 63 1 0
#> 185 24.00 0 44 1 0
#> 35.2 24.00 0 51 0 0
#> 73 24.00 0 NA 0 1
#> 28 24.00 0 67 1 0
#> 144 24.00 0 28 0 1
#> 116 24.00 0 58 0 1
#> 72.1 24.00 0 40 0 1
#> 151.1 24.00 0 42 0 0
#> 161 24.00 0 45 0 0
#> 47.1 24.00 0 38 0 1
#> 27.1 24.00 0 63 1 0
#> 74.2 24.00 0 43 0 1
#> 67 24.00 0 25 0 0
#> 132 24.00 0 55 0 0
#> 11.1 24.00 0 42 0 1
#> 142 24.00 0 53 0 0
#> 178 24.00 0 52 1 0
#> 64.1 24.00 0 43 0 0
#> 115.1 24.00 0 NA 1 0
#> 178.1 24.00 0 52 1 0
#> 94 24.00 0 51 0 1
#> 1 24.00 0 23 1 0
#> 146.3 24.00 0 63 1 0
#> 186 24.00 0 45 1 0
#> 95 24.00 0 68 0 1
#> 53 24.00 0 32 0 1
#> 176 24.00 0 43 0 1
#> 144.1 24.00 0 28 0 1
#> 147 24.00 0 76 1 0
#> 104 24.00 0 50 1 0
#> 19 24.00 0 57 0 1
#> 64.2 24.00 0 43 0 0
#> 84 24.00 0 39 0 1
#> 151.2 24.00 0 42 0 0
#> 151.3 24.00 0 42 0 0
#> 31 24.00 0 36 0 1
#> 19.1 24.00 0 57 0 1
#> 172 24.00 0 41 0 0
#> 116.1 24.00 0 58 0 1
#> 17.2 24.00 0 38 0 1
#> 104.1 24.00 0 50 1 0
#> 116.2 24.00 0 58 0 1
#> 173.1 24.00 0 19 0 1
#> 121 24.00 0 57 1 0
#> 20 24.00 0 46 1 0
#> 31.1 24.00 0 36 0 1
#> 46 24.00 0 71 0 0
#> 104.2 24.00 0 50 1 0
#> 9.1 24.00 0 31 1 0
#> 72.2 24.00 0 40 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.885 NA NA NA
#> 2 age, Cure model 0.0179 NA NA NA
#> 3 grade_ii, Cure model 0.265 NA NA NA
#> 4 grade_iii, Cure model 0.368 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0119 NA NA NA
#> 2 grade_ii, Survival model 0.355 NA NA NA
#> 3 grade_iii, Survival model -0.0579 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.88470 0.01789 0.26481 0.36825
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 258.9
#> Residual Deviance: 254.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.88470239 0.01788684 0.26480711 0.36824527
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01186965 0.35522198 -0.05790933
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.0031437243 0.0074653381 0.6849157663 0.4373720533 0.0198732022
#> [6] 0.0016468756 0.5445985075 0.7119538957 0.0006695393 0.6455453649
#> [11] 0.1699716671 0.6197748393 0.2406954958 0.2503692879 0.1163832206
#> [16] 0.0277810947 0.1305065449 0.4718240726 0.8672889597 0.1699716671
#> [21] 0.2312360377 0.9699411029 0.3484501761 0.3178141483 0.0457583144
#> [26] 0.9403840964 0.8818966372 0.4257634021 0.2033221151 0.2503692879
#> [31] 0.0902432734 0.4030843610 0.0001393007 0.9699411029 0.7811986542
#> [36] 0.3178141483 0.4718240726 0.3178141483 0.2217676740 0.3484501761
#> [41] 0.1095314330 0.7531826819 0.5571463421 0.0104026859 0.1028499761
#> [46] 0.7531826819 0.0198732022 0.9108709428 0.1699716671 0.2503692879
#> [51] 0.6197748393 0.5571463421 0.5943269978 0.9403840964 0.4373720533
#> [56] 0.7256691732 0.3698342583 0.1535309366 0.8096063506 0.4955819360
#> [61] 0.2879987273 0.0457583144 0.0277810947 0.8240239374 0.1456356937
#> [66] 0.5321269834 0.0104026859 0.0457583144 0.0406978003 0.2033221151
#> [71] 0.0778697510 0.4030843610 0.0457583144 0.0457583144 0.7811986542
#> [76] 0.8527683508 0.0778697510 0.1379500181 0.7256691732 0.8818966372
#> [81] 0.2879987273 0.1616619238 0.3698342583 0.6070675880 0.1699716671
#> [86] 0.0104026859 0.6455453649 0.5571463421 0.4955819360 0.0277810947
#> [91] 0.6455453649 0.3918191087 0.3077123968 0.4373720533 0.9108709428
#> [96] 0.0031437243 0.0902432734 0.0715026967 0.6849157663 0.5197517807
#> [101] 0.1163832206 0.2503692879 0.8240239374 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 164 69 56 18 113 168 155 107 86 42 108 177 110
#> 23.60 23.23 12.21 15.21 22.86 23.72 13.08 11.18 23.81 12.43 18.29 12.53 17.56
#> 106 105 197 170 157 183 108.1 40 127 100 188 36 25
#> 16.67 19.75 21.60 19.54 15.10 9.24 18.29 18.00 3.53 16.07 16.16 21.19 6.32
#> 70 29 51 106.1 190 6 24 127.1 61 188.1 157.1 188.2 41
#> 7.38 15.45 18.23 16.67 20.81 15.64 23.89 3.53 10.12 16.16 15.10 16.16 18.02
#> 100.1 158 93 123 92 68 93.1 113.1 77 108.2 106.2 177.1 123.1
#> 16.07 20.14 10.33 13.00 22.92 20.62 10.33 22.86 7.27 18.29 16.67 12.53 13.00
#> 140 25.1 18.1 10 26 97 145 180 192 36.1 197.1 101 76
#> 12.68 6.32 15.21 10.53 15.77 19.14 10.07 14.82 16.44 21.19 21.60 9.97 19.22
#> 81 92.1 36.2 139 51.1 32 6.1 36.3 36.4 61.1 187 32.1 55
#> 14.06 22.92 21.19 21.49 18.23 20.90 15.64 21.19 21.19 10.12 9.92 20.90 19.34
#> 10.1 70.1 85 88 26.1 154 108.3 92.2 42.1 123.2 180.1 197.2 42.2
#> 10.53 7.38 16.44 18.37 15.77 12.63 18.29 22.92 12.43 13.00 14.82 21.60 12.43
#> 125 79 18.2 77.1 164.1 190.1 90 56.1 13 105.1 106.3 101.1 7
#> 15.65 16.23 15.21 7.27 23.60 20.81 20.94 12.21 14.34 19.75 16.67 9.97 24.00
#> 173 34 102 35 182 7.1 27 74 103 135 64 17 11
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 48 196 174 146.1 120 72 191 118 74.1 200 21 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17.1 182.1 119 35.1 9 151 80 47 2 146.2 185 35.2 28
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 116 72.1 151.1 161 47.1 27.1 74.2 67 132 11.1 142 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64.1 178.1 94 1 146.3 186 95 53 176 144.1 147 104 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64.2 84 151.2 151.3 31 19.1 172 116.1 17.2 104.1 116.2 173.1 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 31.1 46 104.2 9.1 72.2
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[84]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01053544 0.34875638 0.32657547
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.3332635 0.0239310 0.2907534
#> grade_iii, Cure model
#> 0.6292616
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 140 12.68 1 59 1 0
#> 85 16.44 1 36 0 0
#> 26 15.77 1 49 0 1
#> 187 9.92 1 39 1 0
#> 153 21.33 1 55 1 0
#> 184 17.77 1 38 0 0
#> 97 19.14 1 65 0 1
#> 145 10.07 1 65 1 0
#> 159 10.55 1 50 0 1
#> 124 9.73 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 188 16.16 1 46 0 1
#> 111 17.45 1 47 0 1
#> 133 14.65 1 57 0 0
#> 117 17.46 1 26 0 1
#> 195 11.76 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 197 21.60 1 69 1 0
#> 123 13.00 1 44 1 0
#> 194 22.40 1 38 0 1
#> 192 16.44 1 31 1 0
#> 52 10.42 1 52 0 1
#> 158 20.14 1 74 1 0
#> 134 17.81 1 47 1 0
#> 16 8.71 1 71 0 1
#> 129 23.41 1 53 1 0
#> 199 19.81 1 NA 0 1
#> 39 15.59 1 37 0 1
#> 167 15.55 1 56 1 0
#> 90 20.94 1 50 0 1
#> 105 19.75 1 60 0 0
#> 93 10.33 1 52 0 1
#> 66 22.13 1 53 0 0
#> 190 20.81 1 42 1 0
#> 91 5.33 1 61 0 1
#> 171 16.57 1 41 0 1
#> 23 16.92 1 61 0 0
#> 43 12.10 1 61 0 1
#> 59 10.16 1 NA 1 0
#> 66.1 22.13 1 53 0 0
#> 177.1 12.53 1 75 0 0
#> 91.1 5.33 1 61 0 1
#> 41 18.02 1 40 1 0
#> 5 16.43 1 51 0 1
#> 110 17.56 1 65 0 1
#> 189 10.51 1 NA 1 0
#> 76 19.22 1 54 0 1
#> 125 15.65 1 67 1 0
#> 36 21.19 1 48 0 1
#> 133.1 14.65 1 57 0 0
#> 139 21.49 1 63 1 0
#> 117.1 17.46 1 26 0 1
#> 61 10.12 1 36 0 1
#> 40 18.00 1 28 1 0
#> 100 16.07 1 60 0 0
#> 90.1 20.94 1 50 0 1
#> 56 12.21 1 60 0 0
#> 168 23.72 1 70 0 0
#> 93.1 10.33 1 52 0 1
#> 18 15.21 1 49 1 0
#> 99 21.19 1 38 0 1
#> 26.1 15.77 1 49 0 1
#> 99.1 21.19 1 38 0 1
#> 179 18.63 1 42 0 0
#> 149 8.37 1 33 1 0
#> 70 7.38 1 30 1 0
#> 124.1 9.73 1 NA 1 0
#> 177.2 12.53 1 75 0 0
#> 29 15.45 1 68 1 0
#> 192.1 16.44 1 31 1 0
#> 42 12.43 1 49 0 1
#> 68 20.62 1 44 0 0
#> 37 12.52 1 57 1 0
#> 41.1 18.02 1 40 1 0
#> 166 19.98 1 48 0 0
#> 52.1 10.42 1 52 0 1
#> 52.2 10.42 1 52 0 1
#> 63 22.77 1 31 1 0
#> 41.2 18.02 1 40 1 0
#> 177.3 12.53 1 75 0 0
#> 5.1 16.43 1 51 0 1
#> 97.1 19.14 1 65 0 1
#> 99.2 21.19 1 38 0 1
#> 41.3 18.02 1 40 1 0
#> 105.1 19.75 1 60 0 0
#> 111.1 17.45 1 47 0 1
#> 125.1 15.65 1 67 1 0
#> 86 23.81 1 58 0 1
#> 85.1 16.44 1 36 0 0
#> 86.1 23.81 1 58 0 1
#> 24 23.89 1 38 0 0
#> 145.1 10.07 1 65 1 0
#> 127 3.53 1 62 0 1
#> 4 17.64 1 NA 0 1
#> 167.1 15.55 1 56 1 0
#> 140.1 12.68 1 59 1 0
#> 43.1 12.10 1 61 0 1
#> 192.2 16.44 1 31 1 0
#> 18.1 15.21 1 49 1 0
#> 36.1 21.19 1 48 0 1
#> 56.1 12.21 1 60 0 0
#> 153.1 21.33 1 55 1 0
#> 194.1 22.40 1 38 0 1
#> 189.1 10.51 1 NA 1 0
#> 180 14.82 1 37 0 0
#> 4.1 17.64 1 NA 0 1
#> 66.2 22.13 1 53 0 0
#> 29.1 15.45 1 68 1 0
#> 169 22.41 1 46 0 0
#> 128 20.35 1 35 0 1
#> 101 9.97 1 10 0 1
#> 91.2 5.33 1 61 0 1
#> 151 24.00 0 42 0 0
#> 53 24.00 0 32 0 1
#> 72 24.00 0 40 0 1
#> 146 24.00 0 63 1 0
#> 11 24.00 0 42 0 1
#> 162 24.00 0 51 0 0
#> 7 24.00 0 37 1 0
#> 193 24.00 0 45 0 1
#> 44 24.00 0 56 0 0
#> 9 24.00 0 31 1 0
#> 132 24.00 0 55 0 0
#> 64 24.00 0 43 0 0
#> 191 24.00 0 60 0 1
#> 17 24.00 0 38 0 1
#> 28 24.00 0 67 1 0
#> 165 24.00 0 47 0 0
#> 147 24.00 0 76 1 0
#> 104 24.00 0 50 1 0
#> 162.1 24.00 0 51 0 0
#> 65 24.00 0 57 1 0
#> 1 24.00 0 23 1 0
#> 196 24.00 0 19 0 0
#> 2 24.00 0 9 0 0
#> 120 24.00 0 68 0 1
#> 72.1 24.00 0 40 0 1
#> 46 24.00 0 71 0 0
#> 193.1 24.00 0 45 0 1
#> 186 24.00 0 45 1 0
#> 53.1 24.00 0 32 0 1
#> 152 24.00 0 36 0 1
#> 48 24.00 0 31 1 0
#> 94 24.00 0 51 0 1
#> 9.1 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 47 24.00 0 38 0 1
#> 162.2 24.00 0 51 0 0
#> 64.1 24.00 0 43 0 0
#> 193.2 24.00 0 45 0 1
#> 1.1 24.00 0 23 1 0
#> 35 24.00 0 51 0 0
#> 147.1 24.00 0 76 1 0
#> 3 24.00 0 31 1 0
#> 193.3 24.00 0 45 0 1
#> 163 24.00 0 66 0 0
#> 28.1 24.00 0 67 1 0
#> 118 24.00 0 44 1 0
#> 115 24.00 0 NA 1 0
#> 191.1 24.00 0 60 0 1
#> 151.1 24.00 0 42 0 0
#> 83 24.00 0 6 0 0
#> 53.2 24.00 0 32 0 1
#> 109 24.00 0 48 0 0
#> 174 24.00 0 49 1 0
#> 178.1 24.00 0 52 1 0
#> 104.1 24.00 0 50 1 0
#> 122 24.00 0 66 0 0
#> 17.1 24.00 0 38 0 1
#> 19 24.00 0 57 0 1
#> 28.2 24.00 0 67 1 0
#> 137 24.00 0 45 1 0
#> 27 24.00 0 63 1 0
#> 176 24.00 0 43 0 1
#> 120.1 24.00 0 68 0 1
#> 53.3 24.00 0 32 0 1
#> 182 24.00 0 35 0 0
#> 118.1 24.00 0 44 1 0
#> 34 24.00 0 36 0 0
#> 19.1 24.00 0 57 0 1
#> 116 24.00 0 58 0 1
#> 48.1 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 28.3 24.00 0 67 1 0
#> 173 24.00 0 19 0 1
#> 151.2 24.00 0 42 0 0
#> 126 24.00 0 48 0 0
#> 173.1 24.00 0 19 0 1
#> 176.1 24.00 0 43 0 1
#> 176.2 24.00 0 43 0 1
#> 112 24.00 0 61 0 0
#> 98 24.00 0 34 1 0
#> 131 24.00 0 66 0 0
#> 148 24.00 0 61 1 0
#> 141 24.00 0 44 1 0
#> 46.1 24.00 0 71 0 0
#> 109.1 24.00 0 48 0 0
#> 198 24.00 0 66 0 1
#> 80 24.00 0 41 0 0
#> 132.1 24.00 0 55 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.33 NA NA NA
#> 2 age, Cure model 0.0239 NA NA NA
#> 3 grade_ii, Cure model 0.291 NA NA NA
#> 4 grade_iii, Cure model 0.629 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0105 NA NA NA
#> 2 grade_ii, Survival model 0.349 NA NA NA
#> 3 grade_iii, Survival model 0.327 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.33326 0.02393 0.29075 0.62926
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 254.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.3332635 0.0239310 0.2907534 0.6292616
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01053544 0.34875638 0.32657547
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.85734542 0.71542952 0.77238052 0.96464032 0.41450477 0.65230937
#> [7] 0.58285221 0.95093569 0.91789208 0.70870952 0.75989358 0.68117957
#> [13] 0.84118208 0.66698196 0.86783847 0.38629827 0.85197468 0.30688277
#> [19] 0.71542952 0.92274828 0.53852805 0.64486008 0.96918349 0.24298805
#> [25] 0.79630814 0.80218102 0.48973598 0.55675422 0.93692910 0.34114949
#> [31] 0.50956876 0.98262987 0.70189761 0.69500983 0.90813602 0.34114949
#> [37] 0.86783847 0.98262987 0.60725253 0.74728396 0.65971702 0.57423548
#> [43] 0.78451496 0.43896563 0.84118208 0.40083583 0.66698196 0.94627487
#> [49] 0.63729495 0.76615948 0.48973598 0.89820543 0.21657757 0.93692910
#> [55] 0.82476879 0.43896563 0.77238052 0.43896563 0.59912300 0.97368596
#> [61] 0.97816756 0.86783847 0.81362391 0.71542952 0.89317718 0.51935167
#> [67] 0.88811121 0.60725253 0.54769103 0.92274828 0.92274828 0.26574927
#> [73] 0.60725253 0.86783847 0.74728396 0.58285221 0.43896563 0.60725253
#> [79] 0.55675422 0.68117957 0.78451496 0.15996055 0.71542952 0.15996055
#> [85] 0.08184601 0.95093569 0.99566684 0.80218102 0.85734542 0.90813602
#> [91] 0.71542952 0.82476879 0.43896563 0.89820543 0.41450477 0.30688277
#> [97] 0.83571039 0.34114949 0.81362391 0.28677516 0.52902712 0.96007268
#> [103] 0.98262987 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 140 85 26 187 153 184 97 145 159 130 188 111 133
#> 12.68 16.44 15.77 9.92 21.33 17.77 19.14 10.07 10.55 16.47 16.16 17.45 14.65
#> 117 177 197 123 194 192 52 158 134 16 129 39 167
#> 17.46 12.53 21.60 13.00 22.40 16.44 10.42 20.14 17.81 8.71 23.41 15.59 15.55
#> 90 105 93 66 190 91 171 23 43 66.1 177.1 91.1 41
#> 20.94 19.75 10.33 22.13 20.81 5.33 16.57 16.92 12.10 22.13 12.53 5.33 18.02
#> 5 110 76 125 36 133.1 139 117.1 61 40 100 90.1 56
#> 16.43 17.56 19.22 15.65 21.19 14.65 21.49 17.46 10.12 18.00 16.07 20.94 12.21
#> 168 93.1 18 99 26.1 99.1 179 149 70 177.2 29 192.1 42
#> 23.72 10.33 15.21 21.19 15.77 21.19 18.63 8.37 7.38 12.53 15.45 16.44 12.43
#> 68 37 41.1 166 52.1 52.2 63 41.2 177.3 5.1 97.1 99.2 41.3
#> 20.62 12.52 18.02 19.98 10.42 10.42 22.77 18.02 12.53 16.43 19.14 21.19 18.02
#> 105.1 111.1 125.1 86 85.1 86.1 24 145.1 127 167.1 140.1 43.1 192.2
#> 19.75 17.45 15.65 23.81 16.44 23.81 23.89 10.07 3.53 15.55 12.68 12.10 16.44
#> 18.1 36.1 56.1 153.1 194.1 180 66.2 29.1 169 128 101 91.2 151
#> 15.21 21.19 12.21 21.33 22.40 14.82 22.13 15.45 22.41 20.35 9.97 5.33 24.00
#> 53 72 146 11 162 7 193 44 9 132 64 191 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 165 147 104 162.1 65 1 196 2 120 72.1 46 193.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 53.1 152 48 94 9.1 178 47 162.2 64.1 193.2 1.1 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147.1 3 193.3 163 28.1 118 191.1 151.1 83 53.2 109 174 178.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104.1 122 17.1 19 28.2 137 27 176 120.1 53.3 182 118.1 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19.1 116 48.1 75 28.3 173 151.2 126 173.1 176.1 176.2 112 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 148 141 46.1 109.1 198 80 132.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[85]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.008258835 1.062187192 0.428132087
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.10874338 0.02191526 0.05460031
#> grade_iii, Cure model
#> 0.72909090
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 30 17.43 1 78 0 0
#> 88 18.37 1 47 0 0
#> 68 20.62 1 44 0 0
#> 66 22.13 1 53 0 0
#> 107 11.18 1 54 1 0
#> 30.1 17.43 1 78 0 0
#> 39 15.59 1 37 0 1
#> 10 10.53 1 34 0 0
#> 113 22.86 1 34 0 0
#> 181 16.46 1 45 0 1
#> 26 15.77 1 49 0 1
#> 39.1 15.59 1 37 0 1
#> 85 16.44 1 36 0 0
#> 188 16.16 1 46 0 1
#> 139 21.49 1 63 1 0
#> 145 10.07 1 65 1 0
#> 192 16.44 1 31 1 0
#> 159 10.55 1 50 0 1
#> 76 19.22 1 54 0 1
#> 25 6.32 1 34 1 0
#> 155 13.08 1 26 0 0
#> 42 12.43 1 49 0 1
#> 18 15.21 1 49 1 0
#> 189 10.51 1 NA 1 0
#> 181.1 16.46 1 45 0 1
#> 168 23.72 1 70 0 0
#> 61 10.12 1 36 0 1
#> 58 19.34 1 39 0 0
#> 78 23.88 1 43 0 0
#> 164 23.60 1 76 0 1
#> 49 12.19 1 48 1 0
#> 140 12.68 1 59 1 0
#> 86 23.81 1 58 0 1
#> 145.1 10.07 1 65 1 0
#> 184 17.77 1 38 0 0
#> 86.1 23.81 1 58 0 1
#> 5 16.43 1 51 0 1
#> 18.1 15.21 1 49 1 0
#> 26.1 15.77 1 49 0 1
#> 49.1 12.19 1 48 1 0
#> 69 23.23 1 25 0 1
#> 197 21.60 1 69 1 0
#> 4 17.64 1 NA 0 1
#> 24 23.89 1 38 0 0
#> 25.1 6.32 1 34 1 0
#> 153 21.33 1 55 1 0
#> 10.1 10.53 1 34 0 0
#> 194 22.40 1 38 0 1
#> 183 9.24 1 67 1 0
#> 85.1 16.44 1 36 0 0
#> 41 18.02 1 40 1 0
#> 124 9.73 1 NA 1 0
#> 140.1 12.68 1 59 1 0
#> 77 7.27 1 67 0 1
#> 8 18.43 1 32 0 0
#> 51 18.23 1 83 0 1
#> 184.1 17.77 1 38 0 0
#> 59 10.16 1 NA 1 0
#> 187 9.92 1 39 1 0
#> 168.1 23.72 1 70 0 0
#> 171 16.57 1 41 0 1
#> 59.1 10.16 1 NA 1 0
#> 114 13.68 1 NA 0 0
#> 149 8.37 1 33 1 0
#> 133 14.65 1 57 0 0
#> 85.2 16.44 1 36 0 0
#> 81 14.06 1 34 0 0
#> 43 12.10 1 61 0 1
#> 188.1 16.16 1 46 0 1
#> 79 16.23 1 54 1 0
#> 55 19.34 1 69 0 1
#> 51.1 18.23 1 83 0 1
#> 110 17.56 1 65 0 1
#> 199 19.81 1 NA 0 1
#> 15 22.68 1 48 0 0
#> 4.1 17.64 1 NA 0 1
#> 96 14.54 1 33 0 1
#> 99 21.19 1 38 0 1
#> 194.1 22.40 1 38 0 1
#> 110.1 17.56 1 65 0 1
#> 184.2 17.77 1 38 0 0
#> 40 18.00 1 28 1 0
#> 124.1 9.73 1 NA 1 0
#> 66.1 22.13 1 53 0 0
#> 77.1 7.27 1 67 0 1
#> 180 14.82 1 37 0 0
#> 56 12.21 1 60 0 0
#> 150 20.33 1 48 0 0
#> 166 19.98 1 48 0 0
#> 164.1 23.60 1 76 0 1
#> 187.1 9.92 1 39 1 0
#> 43.1 12.10 1 61 0 1
#> 37 12.52 1 57 1 0
#> 150.1 20.33 1 48 0 0
#> 187.2 9.92 1 39 1 0
#> 145.2 10.07 1 65 1 0
#> 97 19.14 1 65 0 1
#> 195 11.76 1 NA 1 0
#> 168.2 23.72 1 70 0 0
#> 42.1 12.43 1 49 0 1
#> 124.2 9.73 1 NA 1 0
#> 37.1 12.52 1 57 1 0
#> 58.1 19.34 1 39 0 0
#> 23 16.92 1 61 0 0
#> 39.2 15.59 1 37 0 1
#> 45 17.42 1 54 0 1
#> 57 14.46 1 45 0 1
#> 40.1 18.00 1 28 1 0
#> 166.1 19.98 1 48 0 0
#> 166.2 19.98 1 48 0 0
#> 32 20.90 1 37 1 0
#> 77.2 7.27 1 67 0 1
#> 53 24.00 0 32 0 1
#> 102 24.00 0 49 0 0
#> 17 24.00 0 38 0 1
#> 73 24.00 0 NA 0 1
#> 193 24.00 0 45 0 1
#> 122 24.00 0 66 0 0
#> 115 24.00 0 NA 1 0
#> 75 24.00 0 21 1 0
#> 21 24.00 0 47 0 0
#> 193.1 24.00 0 45 0 1
#> 138 24.00 0 44 1 0
#> 151 24.00 0 42 0 0
#> 191 24.00 0 60 0 1
#> 174 24.00 0 49 1 0
#> 119 24.00 0 17 0 0
#> 148 24.00 0 61 1 0
#> 34 24.00 0 36 0 0
#> 146 24.00 0 63 1 0
#> 72 24.00 0 40 0 1
#> 94 24.00 0 51 0 1
#> 176 24.00 0 43 0 1
#> 138.1 24.00 0 44 1 0
#> 12 24.00 0 63 0 0
#> 196 24.00 0 19 0 0
#> 122.1 24.00 0 66 0 0
#> 193.2 24.00 0 45 0 1
#> 53.1 24.00 0 32 0 1
#> 1 24.00 0 23 1 0
#> 17.1 24.00 0 38 0 1
#> 62 24.00 0 71 0 0
#> 163 24.00 0 66 0 0
#> 64 24.00 0 43 0 0
#> 17.2 24.00 0 38 0 1
#> 7 24.00 0 37 1 0
#> 152 24.00 0 36 0 1
#> 28 24.00 0 67 1 0
#> 74 24.00 0 43 0 1
#> 53.2 24.00 0 32 0 1
#> 198 24.00 0 66 0 1
#> 103 24.00 0 56 1 0
#> 112 24.00 0 61 0 0
#> 48 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 200 24.00 0 64 0 0
#> 2 24.00 0 9 0 0
#> 178 24.00 0 52 1 0
#> 17.3 24.00 0 38 0 1
#> 137 24.00 0 45 1 0
#> 122.2 24.00 0 66 0 0
#> 132 24.00 0 55 0 0
#> 20 24.00 0 46 1 0
#> 196.1 24.00 0 19 0 0
#> 147 24.00 0 76 1 0
#> 109 24.00 0 48 0 0
#> 47 24.00 0 38 0 1
#> 35 24.00 0 51 0 0
#> 98 24.00 0 34 1 0
#> 44 24.00 0 56 0 0
#> 21.1 24.00 0 47 0 0
#> 116 24.00 0 58 0 1
#> 156 24.00 0 50 1 0
#> 109.1 24.00 0 48 0 0
#> 34.1 24.00 0 36 0 0
#> 162 24.00 0 51 0 0
#> 122.3 24.00 0 66 0 0
#> 83 24.00 0 6 0 0
#> 7.1 24.00 0 37 1 0
#> 174.1 24.00 0 49 1 0
#> 83.1 24.00 0 6 0 0
#> 172 24.00 0 41 0 0
#> 102.1 24.00 0 49 0 0
#> 87 24.00 0 27 0 0
#> 118 24.00 0 44 1 0
#> 142 24.00 0 53 0 0
#> 141 24.00 0 44 1 0
#> 104 24.00 0 50 1 0
#> 132.1 24.00 0 55 0 0
#> 75.1 24.00 0 21 1 0
#> 38 24.00 0 31 1 0
#> 44.1 24.00 0 56 0 0
#> 44.2 24.00 0 56 0 0
#> 185 24.00 0 44 1 0
#> 138.2 24.00 0 44 1 0
#> 64.1 24.00 0 43 0 0
#> 9 24.00 0 31 1 0
#> 112.1 24.00 0 61 0 0
#> 20.1 24.00 0 46 1 0
#> 138.3 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.11 NA NA NA
#> 2 age, Cure model 0.0219 NA NA NA
#> 3 grade_ii, Cure model 0.0546 NA NA NA
#> 4 grade_iii, Cure model 0.729 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00826 NA NA NA
#> 2 grade_ii, Survival model 1.06 NA NA NA
#> 3 grade_iii, Survival model 0.428 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.10874 0.02192 0.05460 0.72909
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258
#> Residual Deviance: 248.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.10874338 0.02191526 0.05460031 0.72909090
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.008258835 1.062187192 0.428132087
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.449690701 0.335725028 0.212057929 0.136493103 0.839091066 0.449690701
#> [7] 0.625017457 0.857766397 0.091903583 0.502183246 0.604703341 0.625017457
#> [13] 0.523079804 0.584373086 0.170840720 0.885809294 0.523079804 0.848429517
#> [19] 0.303265806 0.982944500 0.724423868 0.772944312 0.655050657 0.502183246
#> [25] 0.032964575 0.876437508 0.272119119 0.008996401 0.059955067 0.801622776
#> [31] 0.734425353 0.018088648 0.885809294 0.399350545 0.018088648 0.563668298
#> [37] 0.655050657 0.604703341 0.801622776 0.080978641 0.159454891 0.002289102
#> [43] 0.982944500 0.181706164 0.857766397 0.114828544 0.939403801 0.523079804
#> [49] 0.368697719 0.734425353 0.956940463 0.324836469 0.346728415 0.399350545
#> [55] 0.913037423 0.032964575 0.491598151 0.948220885 0.684585966 0.523079804
#> [61] 0.714448996 0.820341325 0.584373086 0.574100198 0.272119119 0.346728415
#> [67] 0.429351013 0.103157268 0.694559059 0.192054220 0.114828544 0.429351013
#> [73] 0.399350545 0.379498609 0.136493103 0.956940463 0.674667129 0.791994288
#> [79] 0.221918308 0.241766119 0.059955067 0.913037423 0.820341325 0.753883214
#> [85] 0.221918308 0.913037423 0.885809294 0.314032046 0.032964575 0.772944312
#> [91] 0.753883214 0.272119119 0.480991679 0.625017457 0.470476974 0.704508105
#> [97] 0.379498609 0.241766119 0.241766119 0.202335349 0.956940463 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 30 88 68 66 107 30.1 39 10 113 181 26 39.1 85
#> 17.43 18.37 20.62 22.13 11.18 17.43 15.59 10.53 22.86 16.46 15.77 15.59 16.44
#> 188 139 145 192 159 76 25 155 42 18 181.1 168 61
#> 16.16 21.49 10.07 16.44 10.55 19.22 6.32 13.08 12.43 15.21 16.46 23.72 10.12
#> 58 78 164 49 140 86 145.1 184 86.1 5 18.1 26.1 49.1
#> 19.34 23.88 23.60 12.19 12.68 23.81 10.07 17.77 23.81 16.43 15.21 15.77 12.19
#> 69 197 24 25.1 153 10.1 194 183 85.1 41 140.1 77 8
#> 23.23 21.60 23.89 6.32 21.33 10.53 22.40 9.24 16.44 18.02 12.68 7.27 18.43
#> 51 184.1 187 168.1 171 149 133 85.2 81 43 188.1 79 55
#> 18.23 17.77 9.92 23.72 16.57 8.37 14.65 16.44 14.06 12.10 16.16 16.23 19.34
#> 51.1 110 15 96 99 194.1 110.1 184.2 40 66.1 77.1 180 56
#> 18.23 17.56 22.68 14.54 21.19 22.40 17.56 17.77 18.00 22.13 7.27 14.82 12.21
#> 150 166 164.1 187.1 43.1 37 150.1 187.2 145.2 97 168.2 42.1 37.1
#> 20.33 19.98 23.60 9.92 12.10 12.52 20.33 9.92 10.07 19.14 23.72 12.43 12.52
#> 58.1 23 39.2 45 57 40.1 166.1 166.2 32 77.2 53 102 17
#> 19.34 16.92 15.59 17.42 14.46 18.00 19.98 19.98 20.90 7.27 24.00 24.00 24.00
#> 193 122 75 21 193.1 138 151 191 174 119 148 34 146
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72 94 176 138.1 12 196 122.1 193.2 53.1 1 17.1 62 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 17.2 7 152 28 74 53.2 198 103 112 48 71 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 178 17.3 137 122.2 132 20 196.1 147 109 47 35 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 21.1 116 156 109.1 34.1 162 122.3 83 7.1 174.1 83.1 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102.1 87 118 142 141 104 132.1 75.1 38 44.1 44.2 185 138.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64.1 9 112.1 20.1 138.3
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[86]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01488969 0.38305121 0.21049700
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.42232942 0.01166874 -0.26531902
#> grade_iii, Cure model
#> 0.51079906
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 164 23.60 1 76 0 1
#> 177 12.53 1 75 0 0
#> 101 9.97 1 10 0 1
#> 189 10.51 1 NA 1 0
#> 190 20.81 1 42 1 0
#> 26 15.77 1 49 0 1
#> 49 12.19 1 48 1 0
#> 39 15.59 1 37 0 1
#> 101.1 9.97 1 10 0 1
#> 85 16.44 1 36 0 0
#> 66 22.13 1 53 0 0
#> 157 15.10 1 47 0 0
#> 56 12.21 1 60 0 0
#> 57 14.46 1 45 0 1
#> 134 17.81 1 47 1 0
#> 153 21.33 1 55 1 0
#> 188 16.16 1 46 0 1
#> 149 8.37 1 33 1 0
#> 81 14.06 1 34 0 0
#> 125 15.65 1 67 1 0
#> 16 8.71 1 71 0 1
#> 70 7.38 1 30 1 0
#> 117 17.46 1 26 0 1
#> 134.1 17.81 1 47 1 0
#> 8 18.43 1 32 0 0
#> 100 16.07 1 60 0 0
#> 32 20.90 1 37 1 0
#> 81.1 14.06 1 34 0 0
#> 85.1 16.44 1 36 0 0
#> 150 20.33 1 48 0 0
#> 49.1 12.19 1 48 1 0
#> 6 15.64 1 39 0 0
#> 24 23.89 1 38 0 0
#> 60 13.15 1 38 1 0
#> 32.1 20.90 1 37 1 0
#> 32.2 20.90 1 37 1 0
#> 36 21.19 1 48 0 1
#> 55 19.34 1 69 0 1
#> 133 14.65 1 57 0 0
#> 6.1 15.64 1 39 0 0
#> 101.2 9.97 1 10 0 1
#> 85.2 16.44 1 36 0 0
#> 127 3.53 1 62 0 1
#> 69 23.23 1 25 0 1
#> 16.1 8.71 1 71 0 1
#> 59 10.16 1 NA 1 0
#> 105 19.75 1 60 0 0
#> 57.1 14.46 1 45 0 1
#> 90 20.94 1 50 0 1
#> 171 16.57 1 41 0 1
#> 91 5.33 1 61 0 1
#> 56.1 12.21 1 60 0 0
#> 29 15.45 1 68 1 0
#> 169 22.41 1 46 0 0
#> 99 21.19 1 38 0 1
#> 158 20.14 1 74 1 0
#> 164.1 23.60 1 76 0 1
#> 168 23.72 1 70 0 0
#> 97 19.14 1 65 0 1
#> 101.3 9.97 1 10 0 1
#> 43 12.10 1 61 0 1
#> 18 15.21 1 49 1 0
#> 6.2 15.64 1 39 0 0
#> 170 19.54 1 43 0 1
#> 180 14.82 1 37 0 0
#> 68 20.62 1 44 0 0
#> 113 22.86 1 34 0 0
#> 43.1 12.10 1 61 0 1
#> 88 18.37 1 47 0 0
#> 150.1 20.33 1 48 0 0
#> 57.2 14.46 1 45 0 1
#> 96 14.54 1 33 0 1
#> 166 19.98 1 48 0 0
#> 41 18.02 1 40 1 0
#> 6.3 15.64 1 39 0 0
#> 14 12.89 1 21 0 0
#> 189.1 10.51 1 NA 1 0
#> 77 7.27 1 67 0 1
#> 90.1 20.94 1 50 0 1
#> 192 16.44 1 31 1 0
#> 77.1 7.27 1 67 0 1
#> 6.4 15.64 1 39 0 0
#> 149.1 8.37 1 33 1 0
#> 195 11.76 1 NA 1 0
#> 108 18.29 1 39 0 1
#> 55.1 19.34 1 69 0 1
#> 175 21.91 1 43 0 0
#> 70.1 7.38 1 30 1 0
#> 175.1 21.91 1 43 0 0
#> 86 23.81 1 58 0 1
#> 114 13.68 1 NA 0 0
#> 157.1 15.10 1 47 0 0
#> 77.2 7.27 1 67 0 1
#> 164.2 23.60 1 76 0 1
#> 89 11.44 1 NA 0 0
#> 128 20.35 1 35 0 1
#> 181 16.46 1 45 0 1
#> 39.1 15.59 1 37 0 1
#> 108.1 18.29 1 39 0 1
#> 96.1 14.54 1 33 0 1
#> 108.2 18.29 1 39 0 1
#> 30 17.43 1 78 0 0
#> 124 9.73 1 NA 1 0
#> 105.1 19.75 1 60 0 0
#> 49.2 12.19 1 48 1 0
#> 4 17.64 1 NA 0 1
#> 96.2 14.54 1 33 0 1
#> 41.1 18.02 1 40 1 0
#> 155 13.08 1 26 0 0
#> 125.1 15.65 1 67 1 0
#> 14.1 12.89 1 21 0 0
#> 195.1 11.76 1 NA 1 0
#> 156 24.00 0 50 1 0
#> 1 24.00 0 23 1 0
#> 176 24.00 0 43 0 1
#> 102 24.00 0 49 0 0
#> 11 24.00 0 42 0 1
#> 22 24.00 0 52 1 0
#> 141 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 185 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 84 24.00 0 39 0 1
#> 38 24.00 0 31 1 0
#> 102.1 24.00 0 49 0 0
#> 132 24.00 0 55 0 0
#> 9 24.00 0 31 1 0
#> 115 24.00 0 NA 1 0
#> 185.1 24.00 0 44 1 0
#> 34 24.00 0 36 0 0
#> 119 24.00 0 17 0 0
#> 185.2 24.00 0 44 1 0
#> 144 24.00 0 28 0 1
#> 95 24.00 0 68 0 1
#> 160 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 132.1 24.00 0 55 0 0
#> 102.2 24.00 0 49 0 0
#> 116 24.00 0 58 0 1
#> 119.1 24.00 0 17 0 0
#> 196 24.00 0 19 0 0
#> 152 24.00 0 36 0 1
#> 80 24.00 0 41 0 0
#> 115.1 24.00 0 NA 1 0
#> 34.1 24.00 0 36 0 0
#> 71 24.00 0 51 0 0
#> 191.1 24.00 0 60 0 1
#> 3 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 191.2 24.00 0 60 0 1
#> 31 24.00 0 36 0 1
#> 82.1 24.00 0 34 0 0
#> 165 24.00 0 47 0 0
#> 135 24.00 0 58 1 0
#> 9.1 24.00 0 31 1 0
#> 35 24.00 0 51 0 0
#> 103 24.00 0 56 1 0
#> 176.1 24.00 0 43 0 1
#> 27 24.00 0 63 1 0
#> 144.1 24.00 0 28 0 1
#> 151 24.00 0 42 0 0
#> 47 24.00 0 38 0 1
#> 83 24.00 0 6 0 0
#> 94 24.00 0 51 0 1
#> 22.1 24.00 0 52 1 0
#> 109 24.00 0 48 0 0
#> 35.1 24.00 0 51 0 0
#> 115.2 24.00 0 NA 1 0
#> 162 24.00 0 51 0 0
#> 38.1 24.00 0 31 1 0
#> 121 24.00 0 57 1 0
#> 47.1 24.00 0 38 0 1
#> 143 24.00 0 51 0 0
#> 200 24.00 0 64 0 0
#> 163 24.00 0 66 0 0
#> 172 24.00 0 41 0 0
#> 83.1 24.00 0 6 0 0
#> 48 24.00 0 31 1 0
#> 102.3 24.00 0 49 0 0
#> 80.1 24.00 0 41 0 0
#> 178 24.00 0 52 1 0
#> 102.4 24.00 0 49 0 0
#> 118 24.00 0 44 1 0
#> 75 24.00 0 21 1 0
#> 173 24.00 0 19 0 1
#> 20 24.00 0 46 1 0
#> 165.1 24.00 0 47 0 0
#> 73 24.00 0 NA 0 1
#> 182 24.00 0 35 0 0
#> 172.1 24.00 0 41 0 0
#> 162.1 24.00 0 51 0 0
#> 22.2 24.00 0 52 1 0
#> 28 24.00 0 67 1 0
#> 94.1 24.00 0 51 0 1
#> 74 24.00 0 43 0 1
#> 82.2 24.00 0 34 0 0
#> 148 24.00 0 61 1 0
#> 94.2 24.00 0 51 0 1
#> 116.1 24.00 0 58 0 1
#> 11.1 24.00 0 42 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.422 NA NA NA
#> 2 age, Cure model 0.0117 NA NA NA
#> 3 grade_ii, Cure model -0.265 NA NA NA
#> 4 grade_iii, Cure model 0.511 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0149 NA NA NA
#> 2 grade_ii, Survival model 0.383 NA NA NA
#> 3 grade_iii, Survival model 0.210 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.42233 0.01167 -0.26532 0.51080
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.3
#> Residual Deviance: 251.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.42232942 0.01166874 -0.26531902 0.51079906
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01488969 0.38305121 0.21049700
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 2.504198e-03 6.660346e-01 7.789674e-01 6.668205e-02 3.278994e-01
#> [6] 7.077795e-01 4.142558e-01 7.789674e-01 2.688922e-01 1.653688e-02
#> [11] 4.610999e-01 6.798217e-01 5.476102e-01 2.131991e-01 2.798117e-02
#> [16] 3.072824e-01 8.649407e-01 5.859798e-01 3.384422e-01 8.355667e-01
#> [21] 8.944176e-01 2.310751e-01 2.131991e-01 1.538519e-01 3.174920e-01
#> [26] 5.166981e-02 5.859798e-01 2.688922e-01 8.381751e-02 7.077795e-01
#> [31] 3.598013e-01 8.580187e-05 6.123090e-01 5.166981e-02 5.166981e-02
#> [36] 3.245078e-02 1.305432e-01 4.976527e-01 3.598013e-01 7.789674e-01
#> [41] 2.688922e-01 9.844749e-01 7.817794e-03 8.355667e-01 1.091764e-01
#> [46] 5.476102e-01 4.159924e-02 2.496756e-01 9.690736e-01 6.798217e-01
#> [51] 4.373276e-01 1.330125e-02 3.245078e-02 9.596479e-02 2.504198e-03
#> [56] 1.251066e-03 1.457886e-01 7.789674e-01 7.499989e-01 4.491677e-01
#> [61] 3.598013e-01 1.231797e-01 4.852773e-01 7.221432e-02 1.041530e-02
#> [66] 7.499989e-01 1.620787e-01 8.381751e-02 5.476102e-01 5.102067e-01
#> [71] 1.024619e-01 1.957214e-01 3.598013e-01 6.391166e-01 9.239546e-01
#> [76] 4.159924e-02 2.688922e-01 9.239546e-01 3.598013e-01 8.649407e-01
#> [81] 1.705212e-01 1.305432e-01 2.016063e-02 8.944176e-01 2.016063e-02
#> [86] 4.991521e-04 4.610999e-01 9.239546e-01 2.504198e-03 7.795821e-02
#> [91] 2.592183e-01 4.142558e-01 1.705212e-01 5.102067e-01 1.705212e-01
#> [96] 2.402517e-01 1.091764e-01 7.077795e-01 5.102067e-01 1.957214e-01
#> [101] 6.256667e-01 3.384422e-01 6.391166e-01 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00
#>
#> $Time
#> 164 177 101 190 26 49 39 101.1 85 66 157 56 57
#> 23.60 12.53 9.97 20.81 15.77 12.19 15.59 9.97 16.44 22.13 15.10 12.21 14.46
#> 134 153 188 149 81 125 16 70 117 134.1 8 100 32
#> 17.81 21.33 16.16 8.37 14.06 15.65 8.71 7.38 17.46 17.81 18.43 16.07 20.90
#> 81.1 85.1 150 49.1 6 24 60 32.1 32.2 36 55 133 6.1
#> 14.06 16.44 20.33 12.19 15.64 23.89 13.15 20.90 20.90 21.19 19.34 14.65 15.64
#> 101.2 85.2 127 69 16.1 105 57.1 90 171 91 56.1 29 169
#> 9.97 16.44 3.53 23.23 8.71 19.75 14.46 20.94 16.57 5.33 12.21 15.45 22.41
#> 99 158 164.1 168 97 101.3 43 18 6.2 170 180 68 113
#> 21.19 20.14 23.60 23.72 19.14 9.97 12.10 15.21 15.64 19.54 14.82 20.62 22.86
#> 43.1 88 150.1 57.2 96 166 41 6.3 14 77 90.1 192 77.1
#> 12.10 18.37 20.33 14.46 14.54 19.98 18.02 15.64 12.89 7.27 20.94 16.44 7.27
#> 6.4 149.1 108 55.1 175 70.1 175.1 86 157.1 77.2 164.2 128 181
#> 15.64 8.37 18.29 19.34 21.91 7.38 21.91 23.81 15.10 7.27 23.60 20.35 16.46
#> 39.1 108.1 96.1 108.2 30 105.1 49.2 96.2 41.1 155 125.1 14.1 156
#> 15.59 18.29 14.54 18.29 17.43 19.75 12.19 14.54 18.02 13.08 15.65 12.89 24.00
#> 1 176 102 11 22 141 146 185 82 84 38 102.1 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 185.1 34 119 185.2 144 95 160 191 132.1 102.2 116 119.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 152 80 34.1 71 191.1 3 72 191.2 31 82.1 165 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.1 35 103 176.1 27 144.1 151 47 83 94 22.1 109 35.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 38.1 121 47.1 143 200 163 172 83.1 48 102.3 80.1 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102.4 118 75 173 20 165.1 182 172.1 162.1 22.2 28 94.1 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82.2 148 94.2 116.1 11.1
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[87]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.007012315 0.329947770 0.407643668
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.63057789 0.01972505 -0.53181502
#> grade_iii, Cure model
#> 0.30320209
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 127 3.53 1 62 0 1
#> 76 19.22 1 54 0 1
#> 128 20.35 1 35 0 1
#> 23 16.92 1 61 0 0
#> 150 20.33 1 48 0 0
#> 79 16.23 1 54 1 0
#> 136 21.83 1 43 0 1
#> 60 13.15 1 38 1 0
#> 66 22.13 1 53 0 0
#> 171 16.57 1 41 0 1
#> 23.1 16.92 1 61 0 0
#> 177 12.53 1 75 0 0
#> 13 14.34 1 54 0 1
#> 139 21.49 1 63 1 0
#> 111 17.45 1 47 0 1
#> 139.1 21.49 1 63 1 0
#> 66.1 22.13 1 53 0 0
#> 168 23.72 1 70 0 0
#> 96 14.54 1 33 0 1
#> 55 19.34 1 69 0 1
#> 8 18.43 1 32 0 0
#> 184 17.77 1 38 0 0
#> 79.1 16.23 1 54 1 0
#> 81 14.06 1 34 0 0
#> 171.1 16.57 1 41 0 1
#> 159 10.55 1 50 0 1
#> 26 15.77 1 49 0 1
#> 97 19.14 1 65 0 1
#> 63 22.77 1 31 1 0
#> 187 9.92 1 39 1 0
#> 100 16.07 1 60 0 0
#> 6 15.64 1 39 0 0
#> 168.1 23.72 1 70 0 0
#> 66.2 22.13 1 53 0 0
#> 70 7.38 1 30 1 0
#> 52 10.42 1 52 0 1
#> 157 15.10 1 47 0 0
#> 188 16.16 1 46 0 1
#> 41 18.02 1 40 1 0
#> 181 16.46 1 45 0 1
#> 169 22.41 1 46 0 0
#> 170 19.54 1 43 0 1
#> 52.1 10.42 1 52 0 1
#> 60.1 13.15 1 38 1 0
#> 168.2 23.72 1 70 0 0
#> 52.2 10.42 1 52 0 1
#> 134 17.81 1 47 1 0
#> 42 12.43 1 49 0 1
#> 91 5.33 1 61 0 1
#> 168.3 23.72 1 70 0 0
#> 149 8.37 1 33 1 0
#> 30 17.43 1 78 0 0
#> 56 12.21 1 60 0 0
#> 154 12.63 1 20 1 0
#> 89 11.44 1 NA 0 0
#> 24 23.89 1 38 0 0
#> 180 14.82 1 37 0 0
#> 111.1 17.45 1 47 0 1
#> 70.1 7.38 1 30 1 0
#> 69 23.23 1 25 0 1
#> 159.1 10.55 1 50 0 1
#> 23.2 16.92 1 61 0 0
#> 40 18.00 1 28 1 0
#> 140 12.68 1 59 1 0
#> 59 10.16 1 NA 1 0
#> 50 10.02 1 NA 1 0
#> 59.1 10.16 1 NA 1 0
#> 194 22.40 1 38 0 1
#> 56.1 12.21 1 60 0 0
#> 61 10.12 1 36 0 1
#> 16 8.71 1 71 0 1
#> 42.1 12.43 1 49 0 1
#> 86 23.81 1 58 0 1
#> 81.1 14.06 1 34 0 0
#> 23.3 16.92 1 61 0 0
#> 45 17.42 1 54 0 1
#> 123 13.00 1 44 1 0
#> 30.1 17.43 1 78 0 0
#> 100.1 16.07 1 60 0 0
#> 123.1 13.00 1 44 1 0
#> 55.1 19.34 1 69 0 1
#> 32 20.90 1 37 1 0
#> 179 18.63 1 42 0 0
#> 155 13.08 1 26 0 0
#> 68 20.62 1 44 0 0
#> 6.1 15.64 1 39 0 0
#> 197 21.60 1 69 1 0
#> 197.1 21.60 1 69 1 0
#> 108 18.29 1 39 0 1
#> 136.1 21.83 1 43 0 1
#> 68.1 20.62 1 44 0 0
#> 129 23.41 1 53 1 0
#> 14 12.89 1 21 0 0
#> 56.2 12.21 1 60 0 0
#> 179.1 18.63 1 42 0 0
#> 107 11.18 1 54 1 0
#> 108.1 18.29 1 39 0 1
#> 97.1 19.14 1 65 0 1
#> 61.1 10.12 1 36 0 1
#> 153 21.33 1 55 1 0
#> 99 21.19 1 38 0 1
#> 110 17.56 1 65 0 1
#> 10 10.53 1 34 0 0
#> 100.2 16.07 1 60 0 0
#> 77 7.27 1 67 0 1
#> 153.1 21.33 1 55 1 0
#> 113 22.86 1 34 0 0
#> 134.1 17.81 1 47 1 0
#> 91.1 5.33 1 61 0 1
#> 113.1 22.86 1 34 0 0
#> 130 16.47 1 53 0 1
#> 180.1 14.82 1 37 0 0
#> 165 24.00 0 47 0 0
#> 35 24.00 0 51 0 0
#> 11 24.00 0 42 0 1
#> 3 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 54 24.00 0 53 1 0
#> 22 24.00 0 52 1 0
#> 48 24.00 0 31 1 0
#> 198 24.00 0 66 0 1
#> 31 24.00 0 36 0 1
#> 65 24.00 0 57 1 0
#> 119 24.00 0 17 0 0
#> 62 24.00 0 71 0 0
#> 115 24.00 0 NA 1 0
#> 160 24.00 0 31 1 0
#> 132 24.00 0 55 0 0
#> 198.1 24.00 0 66 0 1
#> 31.1 24.00 0 36 0 1
#> 2 24.00 0 9 0 0
#> 151 24.00 0 42 0 0
#> 112 24.00 0 61 0 0
#> 151.1 24.00 0 42 0 0
#> 120 24.00 0 68 0 1
#> 98 24.00 0 34 1 0
#> 174 24.00 0 49 1 0
#> 35.1 24.00 0 51 0 0
#> 182 24.00 0 35 0 0
#> 104 24.00 0 50 1 0
#> 185 24.00 0 44 1 0
#> 120.1 24.00 0 68 0 1
#> 118 24.00 0 44 1 0
#> 21 24.00 0 47 0 0
#> 20 24.00 0 46 1 0
#> 102 24.00 0 49 0 0
#> 143 24.00 0 51 0 0
#> 156 24.00 0 50 1 0
#> 119.1 24.00 0 17 0 0
#> 1 24.00 0 23 1 0
#> 196 24.00 0 19 0 0
#> 38 24.00 0 31 1 0
#> 151.2 24.00 0 42 0 0
#> 65.1 24.00 0 57 1 0
#> 7 24.00 0 37 1 0
#> 118.1 24.00 0 44 1 0
#> 47 24.00 0 38 0 1
#> 22.1 24.00 0 52 1 0
#> 137 24.00 0 45 1 0
#> 122 24.00 0 66 0 0
#> 161 24.00 0 45 0 0
#> 118.2 24.00 0 44 1 0
#> 160.1 24.00 0 31 1 0
#> 172.1 24.00 0 41 0 0
#> 196.1 24.00 0 19 0 0
#> 11.1 24.00 0 42 0 1
#> 74 24.00 0 43 0 1
#> 82 24.00 0 34 0 0
#> 115.1 24.00 0 NA 1 0
#> 131 24.00 0 66 0 0
#> 72 24.00 0 40 0 1
#> 121 24.00 0 57 1 0
#> 75 24.00 0 21 1 0
#> 198.2 24.00 0 66 0 1
#> 84 24.00 0 39 0 1
#> 193 24.00 0 45 0 1
#> 193.1 24.00 0 45 0 1
#> 33 24.00 0 53 0 0
#> 35.2 24.00 0 51 0 0
#> 31.2 24.00 0 36 0 1
#> 102.1 24.00 0 49 0 0
#> 75.1 24.00 0 21 1 0
#> 143.1 24.00 0 51 0 0
#> 103 24.00 0 56 1 0
#> 74.1 24.00 0 43 0 1
#> 53 24.00 0 32 0 1
#> 174.1 24.00 0 49 1 0
#> 11.2 24.00 0 42 0 1
#> 104.1 24.00 0 50 1 0
#> 48.1 24.00 0 31 1 0
#> 173 24.00 0 19 0 1
#> 54.1 24.00 0 53 1 0
#> 193.2 24.00 0 45 0 1
#> 146 24.00 0 63 1 0
#> 116 24.00 0 58 0 1
#> 148 24.00 0 61 1 0
#> 22.2 24.00 0 52 1 0
#> 122.1 24.00 0 66 0 0
#> 163 24.00 0 66 0 0
#> 146.1 24.00 0 63 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.631 NA NA NA
#> 2 age, Cure model 0.0197 NA NA NA
#> 3 grade_ii, Cure model -0.532 NA NA NA
#> 4 grade_iii, Cure model 0.303 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00701 NA NA NA
#> 2 grade_ii, Survival model 0.330 NA NA NA
#> 3 grade_iii, Survival model 0.408 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.63058 0.01973 -0.53182 0.30320
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 266.4
#> Residual Deviance: 257.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.63057789 0.01972505 -0.53181502 0.30320209
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.007012315 0.329947770 0.407643668
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.989934141 0.272702231 0.227308526 0.447708435 0.236376438 0.523589209
#> [7] 0.121949861 0.679602878 0.096948174 0.485289776 0.447708435 0.759112609
#> [13] 0.649883681 0.156316168 0.401325005 0.156316168 0.096948174 0.015259177
#> [19] 0.639964959 0.254675246 0.318291736 0.382742681 0.523589209 0.659797958
#> [25] 0.485289776 0.829194695 0.581076484 0.281860797 0.071689116 0.909588427
#> [31] 0.552257944 0.590835150 0.015259177 0.096948174 0.939848135 0.859473195
#> [37] 0.610344270 0.542654948 0.345985111 0.513984764 0.079986355 0.245544903
#> [43] 0.859473195 0.679602878 0.015259177 0.859473195 0.364498299 0.769138378
#> [49] 0.969910196 0.015259177 0.929765938 0.419634435 0.789025194 0.749140707
#> [55] 0.002348807 0.620222741 0.401325005 0.939848135 0.047814789 0.829194695
#> [61] 0.447708435 0.355258935 0.739141002 0.088528498 0.789025194 0.889519409
#> [67] 0.919672408 0.769138378 0.008664667 0.659797958 0.447708435 0.438286807
#> [73] 0.709348209 0.419634435 0.552257944 0.709348209 0.254675246 0.200470802
#> [79] 0.299935041 0.699370089 0.209411378 0.590835150 0.138980339 0.138980339
#> [85] 0.327661508 0.121949861 0.209411378 0.039412450 0.729152159 0.789025194
#> [91] 0.299935041 0.819054182 0.327661508 0.281860797 0.889519409 0.173859658
#> [97] 0.191501081 0.392028662 0.849323019 0.552257944 0.959850172 0.173859658
#> [103] 0.055852181 0.364498299 0.969910196 0.055852181 0.504362981 0.620222741
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000 0.000000000
#>
#> $Time
#> 127 76 128 23 150 79 136 60 66 171 23.1 177 13
#> 3.53 19.22 20.35 16.92 20.33 16.23 21.83 13.15 22.13 16.57 16.92 12.53 14.34
#> 139 111 139.1 66.1 168 96 55 8 184 79.1 81 171.1 159
#> 21.49 17.45 21.49 22.13 23.72 14.54 19.34 18.43 17.77 16.23 14.06 16.57 10.55
#> 26 97 63 187 100 6 168.1 66.2 70 52 157 188 41
#> 15.77 19.14 22.77 9.92 16.07 15.64 23.72 22.13 7.38 10.42 15.10 16.16 18.02
#> 181 169 170 52.1 60.1 168.2 52.2 134 42 91 168.3 149 30
#> 16.46 22.41 19.54 10.42 13.15 23.72 10.42 17.81 12.43 5.33 23.72 8.37 17.43
#> 56 154 24 180 111.1 70.1 69 159.1 23.2 40 140 194 56.1
#> 12.21 12.63 23.89 14.82 17.45 7.38 23.23 10.55 16.92 18.00 12.68 22.40 12.21
#> 61 16 42.1 86 81.1 23.3 45 123 30.1 100.1 123.1 55.1 32
#> 10.12 8.71 12.43 23.81 14.06 16.92 17.42 13.00 17.43 16.07 13.00 19.34 20.90
#> 179 155 68 6.1 197 197.1 108 136.1 68.1 129 14 56.2 179.1
#> 18.63 13.08 20.62 15.64 21.60 21.60 18.29 21.83 20.62 23.41 12.89 12.21 18.63
#> 107 108.1 97.1 61.1 153 99 110 10 100.2 77 153.1 113 134.1
#> 11.18 18.29 19.14 10.12 21.33 21.19 17.56 10.53 16.07 7.27 21.33 22.86 17.81
#> 91.1 113.1 130 180.1 165 35 11 3 172 54 22 48 198
#> 5.33 22.86 16.47 14.82 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 65 119 62 160 132 198.1 31.1 2 151 112 151.1 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 174 35.1 182 104 185 120.1 118 21 20 102 143 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119.1 1 196 38 151.2 65.1 7 118.1 47 22.1 137 122 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118.2 160.1 172.1 196.1 11.1 74 82 131 72 121 75 198.2 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 193.1 33 35.2 31.2 102.1 75.1 143.1 103 74.1 53 174.1 11.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104.1 48.1 173 54.1 193.2 146 116 148 22.2 122.1 163 146.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[88]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01502579 0.72640077 0.55584827
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.199726032 0.001568373 0.126086003
#> grade_iii, Cure model
#> 0.882520529
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 184 17.77 1 38 0 0
#> 66 22.13 1 53 0 0
#> 128 20.35 1 35 0 1
#> 52 10.42 1 52 0 1
#> 26 15.77 1 49 0 1
#> 194 22.40 1 38 0 1
#> 90 20.94 1 50 0 1
#> 123 13.00 1 44 1 0
#> 105 19.75 1 60 0 0
#> 16 8.71 1 71 0 1
#> 6 15.64 1 39 0 0
#> 99 21.19 1 38 0 1
#> 86 23.81 1 58 0 1
#> 188 16.16 1 46 0 1
#> 124 9.73 1 NA 1 0
#> 52.1 10.42 1 52 0 1
#> 136 21.83 1 43 0 1
#> 179 18.63 1 42 0 0
#> 30 17.43 1 78 0 0
#> 129 23.41 1 53 1 0
#> 150 20.33 1 48 0 0
#> 175 21.91 1 43 0 0
#> 41 18.02 1 40 1 0
#> 153 21.33 1 55 1 0
#> 169 22.41 1 46 0 0
#> 183 9.24 1 67 1 0
#> 50 10.02 1 NA 1 0
#> 197 21.60 1 69 1 0
#> 170 19.54 1 43 0 1
#> 111 17.45 1 47 0 1
#> 77 7.27 1 67 0 1
#> 68 20.62 1 44 0 0
#> 179.1 18.63 1 42 0 0
#> 14 12.89 1 21 0 0
#> 187 9.92 1 39 1 0
#> 197.1 21.60 1 69 1 0
#> 37 12.52 1 57 1 0
#> 96 14.54 1 33 0 1
#> 4 17.64 1 NA 0 1
#> 42 12.43 1 49 0 1
#> 179.2 18.63 1 42 0 0
#> 5 16.43 1 51 0 1
#> 78 23.88 1 43 0 0
#> 50.1 10.02 1 NA 1 0
#> 41.1 18.02 1 40 1 0
#> 125 15.65 1 67 1 0
#> 36 21.19 1 48 0 1
#> 70 7.38 1 30 1 0
#> 66.1 22.13 1 53 0 0
#> 125.1 15.65 1 67 1 0
#> 14.1 12.89 1 21 0 0
#> 130 16.47 1 53 0 1
#> 153.1 21.33 1 55 1 0
#> 170.1 19.54 1 43 0 1
#> 155 13.08 1 26 0 0
#> 192 16.44 1 31 1 0
#> 100 16.07 1 60 0 0
#> 77.1 7.27 1 67 0 1
#> 24 23.89 1 38 0 0
#> 139 21.49 1 63 1 0
#> 154 12.63 1 20 1 0
#> 97 19.14 1 65 0 1
#> 8 18.43 1 32 0 0
#> 154.1 12.63 1 20 1 0
#> 187.1 9.92 1 39 1 0
#> 52.2 10.42 1 52 0 1
#> 167 15.55 1 56 1 0
#> 78.1 23.88 1 43 0 0
#> 164 23.60 1 76 0 1
#> 108 18.29 1 39 0 1
#> 8.1 18.43 1 32 0 0
#> 197.2 21.60 1 69 1 0
#> 123.1 13.00 1 44 1 0
#> 41.2 18.02 1 40 1 0
#> 40 18.00 1 28 1 0
#> 40.1 18.00 1 28 1 0
#> 50.2 10.02 1 NA 1 0
#> 123.2 13.00 1 44 1 0
#> 171 16.57 1 41 0 1
#> 166 19.98 1 48 0 0
#> 45 17.42 1 54 0 1
#> 77.2 7.27 1 67 0 1
#> 55 19.34 1 69 0 1
#> 158 20.14 1 74 1 0
#> 81 14.06 1 34 0 0
#> 197.3 21.60 1 69 1 0
#> 26.1 15.77 1 49 0 1
#> 117 17.46 1 26 0 1
#> 8.2 18.43 1 32 0 0
#> 86.1 23.81 1 58 0 1
#> 157 15.10 1 47 0 0
#> 106 16.67 1 49 1 0
#> 16.1 8.71 1 71 0 1
#> 78.2 23.88 1 43 0 0
#> 60 13.15 1 38 1 0
#> 68.1 20.62 1 44 0 0
#> 26.2 15.77 1 49 0 1
#> 159 10.55 1 50 0 1
#> 108.1 18.29 1 39 0 1
#> 40.2 18.00 1 28 1 0
#> 55.1 19.34 1 69 0 1
#> 76 19.22 1 54 0 1
#> 92 22.92 1 47 0 1
#> 52.3 10.42 1 52 0 1
#> 184.1 17.77 1 38 0 0
#> 97.1 19.14 1 65 0 1
#> 129.1 23.41 1 53 1 0
#> 194.1 22.40 1 38 0 1
#> 195 11.76 1 NA 1 0
#> 99.1 21.19 1 38 0 1
#> 90.1 20.94 1 50 0 1
#> 16.2 8.71 1 71 0 1
#> 72 24.00 0 40 0 1
#> 163 24.00 0 66 0 0
#> 17 24.00 0 38 0 1
#> 44 24.00 0 56 0 0
#> 138 24.00 0 44 1 0
#> 121 24.00 0 57 1 0
#> 35 24.00 0 51 0 0
#> 48 24.00 0 31 1 0
#> 44.1 24.00 0 56 0 0
#> 71 24.00 0 51 0 0
#> 102 24.00 0 49 0 0
#> 135 24.00 0 58 1 0
#> 20 24.00 0 46 1 0
#> 21 24.00 0 47 0 0
#> 131 24.00 0 66 0 0
#> 142 24.00 0 53 0 0
#> 53 24.00 0 32 0 1
#> 144 24.00 0 28 0 1
#> 151 24.00 0 42 0 0
#> 141 24.00 0 44 1 0
#> 196 24.00 0 19 0 0
#> 64 24.00 0 43 0 0
#> 102.1 24.00 0 49 0 0
#> 9 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 67 24.00 0 25 0 0
#> 191 24.00 0 60 0 1
#> 165 24.00 0 47 0 0
#> 144.1 24.00 0 28 0 1
#> 161 24.00 0 45 0 0
#> 95 24.00 0 68 0 1
#> 193 24.00 0 45 0 1
#> 27 24.00 0 63 1 0
#> 1 24.00 0 23 1 0
#> 95.1 24.00 0 68 0 1
#> 176 24.00 0 43 0 1
#> 165.1 24.00 0 47 0 0
#> 142.1 24.00 0 53 0 0
#> 28 24.00 0 67 1 0
#> 119 24.00 0 17 0 0
#> 132 24.00 0 55 0 0
#> 38 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 3 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 178.1 24.00 0 52 1 0
#> 116 24.00 0 58 0 1
#> 73.1 24.00 0 NA 0 1
#> 38.1 24.00 0 31 1 0
#> 121.1 24.00 0 57 1 0
#> 35.1 24.00 0 51 0 0
#> 38.2 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 20.1 24.00 0 46 1 0
#> 80 24.00 0 41 0 0
#> 112 24.00 0 61 0 0
#> 120 24.00 0 68 0 1
#> 119.1 24.00 0 17 0 0
#> 120.1 24.00 0 68 0 1
#> 87 24.00 0 27 0 0
#> 162 24.00 0 51 0 0
#> 182 24.00 0 35 0 0
#> 104 24.00 0 50 1 0
#> 186 24.00 0 45 1 0
#> 116.1 24.00 0 58 0 1
#> 186.1 24.00 0 45 1 0
#> 116.2 24.00 0 58 0 1
#> 65 24.00 0 57 1 0
#> 186.2 24.00 0 45 1 0
#> 144.2 24.00 0 28 0 1
#> 65.1 24.00 0 57 1 0
#> 46 24.00 0 71 0 0
#> 137.1 24.00 0 45 1 0
#> 54 24.00 0 53 1 0
#> 141.1 24.00 0 44 1 0
#> 143 24.00 0 51 0 0
#> 33 24.00 0 53 0 0
#> 98 24.00 0 34 1 0
#> 64.1 24.00 0 43 0 0
#> 19 24.00 0 57 0 1
#> 7 24.00 0 37 1 0
#> 62 24.00 0 71 0 0
#> 126 24.00 0 48 0 0
#> 156 24.00 0 50 1 0
#> 72.1 24.00 0 40 0 1
#> 135.1 24.00 0 58 1 0
#> 72.2 24.00 0 40 0 1
#> 19.1 24.00 0 57 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.200 NA NA NA
#> 2 age, Cure model 0.00157 NA NA NA
#> 3 grade_ii, Cure model 0.126 NA NA NA
#> 4 grade_iii, Cure model 0.883 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0150 NA NA NA
#> 2 grade_ii, Survival model 0.726 NA NA NA
#> 3 grade_iii, Survival model 0.556 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.199726 0.001568 0.126086 0.882521
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.1
#> Residual Deviance: 257 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.199726032 0.001568373 0.126086003 0.882520529
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01502579 0.72640077 0.55584827
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.4570758166 0.0632723529 0.2013833725 0.8408344782 0.5954983178
#> [6] 0.0510860281 0.1681787199 0.7286394296 0.2369909949 0.9195933819
#> [11] 0.6498041521 0.1448073758 0.0124681418 0.5738417086 0.8408344782
#> [16] 0.0843836056 0.3131431252 0.4988363577 0.0276659409 0.2100406293
#> [21] 0.0769042952 0.3958180892 0.1289400129 0.0446111261 0.9081932153
#> [26] 0.0919209790 0.2463508780 0.4883355225 0.9653983026 0.1844194570
#> [31] 0.3131431252 0.7620788551 0.8856048643 0.0919209790 0.8070170228
#> [36] 0.6833971393 0.8182633708 0.3131431252 0.5630985014 0.0030632633
#> [41] 0.3958180892 0.6278564006 0.1448073758 0.9538755535 0.0632723529
#> [46] 0.6278564006 0.7620788551 0.5416275144 0.1289400129 0.2463508780
#> [51] 0.7172823441 0.5523940603 0.5846104403 0.9653983026 0.0005217745
#> [56] 0.1208451644 0.7847186908 0.2935586468 0.3433624739 0.7847186908
#> [61] 0.8856048643 0.8408344782 0.6609565305 0.0030632633 0.0217447803
#> [66] 0.3746335376 0.3433624739 0.0919209790 0.7286394296 0.3958180892
#> [71] 0.4268391626 0.4268391626 0.7286394296 0.5309065332 0.2278456988
#> [76] 0.5094920262 0.9653983026 0.2648345303 0.2188852350 0.6946534074
#> [81] 0.0919209790 0.5954983178 0.4778661235 0.3433624739 0.0124681418
#> [86] 0.6721293999 0.5201981944 0.9195933819 0.0030632633 0.7059831189
#> [91] 0.1844194570 0.5954983178 0.8295352951 0.3746335376 0.4268391626
#> [96] 0.2648345303 0.2838245423 0.0385741878 0.8408344782 0.4570758166
#> [101] 0.2935586468 0.0276659409 0.0510860281 0.1448073758 0.1681787199
#> [106] 0.9195933819 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [191] 0.0000000000 0.0000000000
#>
#> $Time
#> 184 66 128 52 26 194 90 123 105 16 6 99 86
#> 17.77 22.13 20.35 10.42 15.77 22.40 20.94 13.00 19.75 8.71 15.64 21.19 23.81
#> 188 52.1 136 179 30 129 150 175 41 153 169 183 197
#> 16.16 10.42 21.83 18.63 17.43 23.41 20.33 21.91 18.02 21.33 22.41 9.24 21.60
#> 170 111 77 68 179.1 14 187 197.1 37 96 42 179.2 5
#> 19.54 17.45 7.27 20.62 18.63 12.89 9.92 21.60 12.52 14.54 12.43 18.63 16.43
#> 78 41.1 125 36 70 66.1 125.1 14.1 130 153.1 170.1 155 192
#> 23.88 18.02 15.65 21.19 7.38 22.13 15.65 12.89 16.47 21.33 19.54 13.08 16.44
#> 100 77.1 24 139 154 97 8 154.1 187.1 52.2 167 78.1 164
#> 16.07 7.27 23.89 21.49 12.63 19.14 18.43 12.63 9.92 10.42 15.55 23.88 23.60
#> 108 8.1 197.2 123.1 41.2 40 40.1 123.2 171 166 45 77.2 55
#> 18.29 18.43 21.60 13.00 18.02 18.00 18.00 13.00 16.57 19.98 17.42 7.27 19.34
#> 158 81 197.3 26.1 117 8.2 86.1 157 106 16.1 78.2 60 68.1
#> 20.14 14.06 21.60 15.77 17.46 18.43 23.81 15.10 16.67 8.71 23.88 13.15 20.62
#> 26.2 159 108.1 40.2 55.1 76 92 52.3 184.1 97.1 129.1 194.1 99.1
#> 15.77 10.55 18.29 18.00 19.34 19.22 22.92 10.42 17.77 19.14 23.41 22.40 21.19
#> 90.1 16.2 72 163 17 44 138 121 35 48 44.1 71 102
#> 20.94 8.71 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 20 21 131 142 53 144 151 141 196 64 102.1 9
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 191 165 144.1 161 95 193 27 1 95.1 176 165.1 142.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 119 132 38 47 3 178 178.1 116 38.1 121.1 35.1 38.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 20.1 80 112 120 119.1 120.1 87 162 182 104 186 116.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186.1 116.2 65 186.2 144.2 65.1 46 137.1 54 141.1 143 33 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64.1 19 7 62 126 156 72.1 135.1 72.2 19.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[89]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00952719 0.54260833 0.47810795
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.363463703 -0.004658765 -0.584025181
#> grade_iii, Cure model
#> 0.626463125
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 159 10.55 1 50 0 1
#> 133 14.65 1 57 0 0
#> 111 17.45 1 47 0 1
#> 184 17.77 1 38 0 0
#> 175 21.91 1 43 0 0
#> 16 8.71 1 71 0 1
#> 39 15.59 1 37 0 1
#> 14 12.89 1 21 0 0
#> 175.1 21.91 1 43 0 0
#> 197 21.60 1 69 1 0
#> 171 16.57 1 41 0 1
#> 195 11.76 1 NA 1 0
#> 171.1 16.57 1 41 0 1
#> 197.1 21.60 1 69 1 0
#> 175.2 21.91 1 43 0 0
#> 63 22.77 1 31 1 0
#> 181 16.46 1 45 0 1
#> 66 22.13 1 53 0 0
#> 23 16.92 1 61 0 0
#> 101 9.97 1 10 0 1
#> 101.1 9.97 1 10 0 1
#> 24 23.89 1 38 0 0
#> 81 14.06 1 34 0 0
#> 123 13.00 1 44 1 0
#> 88 18.37 1 47 0 0
#> 124 9.73 1 NA 1 0
#> 51 18.23 1 83 0 1
#> 41 18.02 1 40 1 0
#> 111.1 17.45 1 47 0 1
#> 108 18.29 1 39 0 1
#> 130 16.47 1 53 0 1
#> 85 16.44 1 36 0 0
#> 134 17.81 1 47 1 0
#> 105 19.75 1 60 0 0
#> 61 10.12 1 36 0 1
#> 85.1 16.44 1 36 0 0
#> 61.1 10.12 1 36 0 1
#> 39.1 15.59 1 37 0 1
#> 39.2 15.59 1 37 0 1
#> 52 10.42 1 52 0 1
#> 155 13.08 1 26 0 0
#> 170 19.54 1 43 0 1
#> 117 17.46 1 26 0 1
#> 111.2 17.45 1 47 0 1
#> 106 16.67 1 49 1 0
#> 180 14.82 1 37 0 0
#> 4 17.64 1 NA 0 1
#> 23.1 16.92 1 61 0 0
#> 23.2 16.92 1 61 0 0
#> 149 8.37 1 33 1 0
#> 123.1 13.00 1 44 1 0
#> 59 10.16 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 170.1 19.54 1 43 0 1
#> 154 12.63 1 20 1 0
#> 159.1 10.55 1 50 0 1
#> 128 20.35 1 35 0 1
#> 166 19.98 1 48 0 0
#> 6 15.64 1 39 0 0
#> 5 16.43 1 51 0 1
#> 168 23.72 1 70 0 0
#> 55 19.34 1 69 0 1
#> 166.1 19.98 1 48 0 0
#> 60 13.15 1 38 1 0
#> 175.3 21.91 1 43 0 0
#> 97 19.14 1 65 0 1
#> 52.1 10.42 1 52 0 1
#> 63.1 22.77 1 31 1 0
#> 96 14.54 1 33 0 1
#> 76 19.22 1 54 0 1
#> 99 21.19 1 38 0 1
#> 6.1 15.64 1 39 0 0
#> 184.1 17.77 1 38 0 0
#> 100 16.07 1 60 0 0
#> 108.1 18.29 1 39 0 1
#> 26 15.77 1 49 0 1
#> 150 20.33 1 48 0 0
#> 155.1 13.08 1 26 0 0
#> 85.2 16.44 1 36 0 0
#> 39.3 15.59 1 37 0 1
#> 51.1 18.23 1 83 0 1
#> 107 11.18 1 54 1 0
#> 59.1 10.16 1 NA 1 0
#> 79 16.23 1 54 1 0
#> 30 17.43 1 78 0 0
#> 50 10.02 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 90 20.94 1 50 0 1
#> 140 12.68 1 59 1 0
#> 164 23.60 1 76 0 1
#> 58 19.34 1 39 0 0
#> 171.2 16.57 1 41 0 1
#> 111.3 17.45 1 47 0 1
#> 149.1 8.37 1 33 1 0
#> 175.4 21.91 1 43 0 0
#> 90.1 20.94 1 50 0 1
#> 37 12.52 1 57 1 0
#> 69 23.23 1 25 0 1
#> 43 12.10 1 61 0 1
#> 8 18.43 1 32 0 0
#> 195.1 11.76 1 NA 1 0
#> 51.2 18.23 1 83 0 1
#> 4.1 17.64 1 NA 0 1
#> 16.1 8.71 1 71 0 1
#> 86 23.81 1 58 0 1
#> 158 20.14 1 74 1 0
#> 18 15.21 1 49 1 0
#> 66.1 22.13 1 53 0 0
#> 30.1 17.43 1 78 0 0
#> 179 18.63 1 42 0 0
#> 40 18.00 1 28 1 0
#> 179.1 18.63 1 42 0 0
#> 62 24.00 0 71 0 0
#> 102 24.00 0 49 0 0
#> 191 24.00 0 60 0 1
#> 82 24.00 0 34 0 0
#> 54 24.00 0 53 1 0
#> 198 24.00 0 66 0 1
#> 191.1 24.00 0 60 0 1
#> 178 24.00 0 52 1 0
#> 9 24.00 0 31 1 0
#> 141 24.00 0 44 1 0
#> 75 24.00 0 21 1 0
#> 75.1 24.00 0 21 1 0
#> 147 24.00 0 76 1 0
#> 94 24.00 0 51 0 1
#> 3 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 141.1 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 156 24.00 0 50 1 0
#> 146 24.00 0 63 1 0
#> 82.1 24.00 0 34 0 0
#> 137 24.00 0 45 1 0
#> 20 24.00 0 46 1 0
#> 62.1 24.00 0 71 0 0
#> 67 24.00 0 25 0 0
#> 94.1 24.00 0 51 0 1
#> 48 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 47 24.00 0 38 0 1
#> 151 24.00 0 42 0 0
#> 162 24.00 0 51 0 0
#> 160 24.00 0 31 1 0
#> 151.1 24.00 0 42 0 0
#> 21 24.00 0 47 0 0
#> 193 24.00 0 45 0 1
#> 1 24.00 0 23 1 0
#> 21.1 24.00 0 47 0 0
#> 162.1 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 182 24.00 0 35 0 0
#> 151.2 24.00 0 42 0 0
#> 176 24.00 0 43 0 1
#> 75.2 24.00 0 21 1 0
#> 112 24.00 0 61 0 0
#> 191.2 24.00 0 60 0 1
#> 7.1 24.00 0 37 1 0
#> 62.2 24.00 0 71 0 0
#> 1.1 24.00 0 23 1 0
#> 62.3 24.00 0 71 0 0
#> 75.3 24.00 0 21 1 0
#> 131 24.00 0 66 0 0
#> 22 24.00 0 52 1 0
#> 174 24.00 0 49 1 0
#> 87 24.00 0 27 0 0
#> 19.1 24.00 0 57 0 1
#> 151.3 24.00 0 42 0 0
#> 163 24.00 0 66 0 0
#> 122 24.00 0 66 0 0
#> 95 24.00 0 68 0 1
#> 161 24.00 0 45 0 0
#> 174.1 24.00 0 49 1 0
#> 47.1 24.00 0 38 0 1
#> 132 24.00 0 55 0 0
#> 33 24.00 0 53 0 0
#> 141.2 24.00 0 44 1 0
#> 46 24.00 0 71 0 0
#> 104 24.00 0 50 1 0
#> 182.1 24.00 0 35 0 0
#> 156.1 24.00 0 50 1 0
#> 191.3 24.00 0 60 0 1
#> 80 24.00 0 41 0 0
#> 162.2 24.00 0 51 0 0
#> 120 24.00 0 68 0 1
#> 1.2 24.00 0 23 1 0
#> 121 24.00 0 57 1 0
#> 9.1 24.00 0 31 1 0
#> 131.1 24.00 0 66 0 0
#> 21.2 24.00 0 47 0 0
#> 31.1 24.00 0 36 0 1
#> 73 24.00 0 NA 0 1
#> 137.1 24.00 0 45 1 0
#> 198.1 24.00 0 66 0 1
#> 132.1 24.00 0 55 0 0
#> 84 24.00 0 39 0 1
#> 115 24.00 0 NA 1 0
#> 84.1 24.00 0 39 0 1
#> 135 24.00 0 58 1 0
#> 144 24.00 0 28 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.363 NA NA NA
#> 2 age, Cure model -0.00466 NA NA NA
#> 3 grade_ii, Cure model -0.584 NA NA NA
#> 4 grade_iii, Cure model 0.626 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00953 NA NA NA
#> 2 grade_ii, Survival model 0.543 NA NA NA
#> 3 grade_iii, Survival model 0.478 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.363464 -0.004659 -0.584025 0.626463
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 251.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.363463703 -0.004658765 -0.584025181 0.626463125
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00952719 0.54260833 0.47810795
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.873656354 0.724372288 0.406252029 0.376433221 0.070963199 0.958116314
#> [7] 0.651262981 0.809586858 0.070963199 0.107860987 0.505780942 0.505780942
#> [13] 0.107860987 0.070963199 0.042971053 0.546592518 0.056273330 0.464699612
#> [19] 0.937199555 0.937199555 0.001363562 0.745698859 0.788357385 0.288023660
#> [25] 0.317305311 0.346613691 0.406252029 0.297941603 0.536236776 0.556938344
#> [31] 0.366540585 0.194304326 0.916062790 0.556938344 0.916062790 0.651262981
#> [37] 0.651262981 0.894855250 0.767052595 0.203634584 0.396271224 0.406252029
#> [43] 0.495359754 0.713760789 0.464699612 0.464699612 0.979115557 0.788357385
#> [49] 0.692618610 0.203634584 0.831011331 0.873656354 0.150292907 0.176455912
#> [55] 0.630063408 0.587894782 0.018514699 0.221753837 0.176455912 0.756390639
#> [61] 0.070963199 0.249669069 0.894855250 0.042971053 0.735049330 0.240231921
#> [67] 0.124780800 0.630063408 0.376433221 0.608903289 0.297941603 0.619484371
#> [73] 0.158875071 0.767052595 0.556938344 0.651262981 0.317305311 0.862991373
#> [79] 0.598401664 0.444618846 0.005733622 0.133473854 0.820297743 0.026456346
#> [85] 0.221753837 0.505780942 0.406252029 0.979115557 0.070963199 0.133473854
#> [91] 0.841666950 0.034971864 0.852322630 0.278227496 0.317305311 0.958116314
#> [97] 0.011960048 0.167630897 0.703195953 0.056273330 0.444618846 0.259153451
#> [103] 0.356621336 0.259153451 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 159 133 111 184 175 16 39 14 175.1 197 171 171.1 197.1
#> 10.55 14.65 17.45 17.77 21.91 8.71 15.59 12.89 21.91 21.60 16.57 16.57 21.60
#> 175.2 63 181 66 23 101 101.1 24 81 123 88 51 41
#> 21.91 22.77 16.46 22.13 16.92 9.97 9.97 23.89 14.06 13.00 18.37 18.23 18.02
#> 111.1 108 130 85 134 105 61 85.1 61.1 39.1 39.2 52 155
#> 17.45 18.29 16.47 16.44 17.81 19.75 10.12 16.44 10.12 15.59 15.59 10.42 13.08
#> 170 117 111.2 106 180 23.1 23.2 149 123.1 167 170.1 154 159.1
#> 19.54 17.46 17.45 16.67 14.82 16.92 16.92 8.37 13.00 15.55 19.54 12.63 10.55
#> 128 166 6 5 168 55 166.1 60 175.3 97 52.1 63.1 96
#> 20.35 19.98 15.64 16.43 23.72 19.34 19.98 13.15 21.91 19.14 10.42 22.77 14.54
#> 76 99 6.1 184.1 100 108.1 26 150 155.1 85.2 39.3 51.1 107
#> 19.22 21.19 15.64 17.77 16.07 18.29 15.77 20.33 13.08 16.44 15.59 18.23 11.18
#> 79 30 78 90 140 164 58 171.2 111.3 149.1 175.4 90.1 37
#> 16.23 17.43 23.88 20.94 12.68 23.60 19.34 16.57 17.45 8.37 21.91 20.94 12.52
#> 69 43 8 51.2 16.1 86 158 18 66.1 30.1 179 40 179.1
#> 23.23 12.10 18.43 18.23 8.71 23.81 20.14 15.21 22.13 17.43 18.63 18.00 18.63
#> 62 102 191 82 54 198 191.1 178 9 141 75 75.1 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 3 119 141.1 31 156 146 82.1 137 20 62.1 67 94.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 7 47 151 162 160 151.1 21 193 1 21.1 162.1 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 151.2 176 75.2 112 191.2 7.1 62.2 1.1 62.3 75.3 131 22
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 87 19.1 151.3 163 122 95 161 174.1 47.1 132 33 141.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46 104 182.1 156.1 191.3 80 162.2 120 1.2 121 9.1 131.1 21.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31.1 137.1 198.1 132.1 84 84.1 135 144
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[90]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.005534736 0.824736985 0.367594950
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.031731934 0.001237403 -0.298337912
#> grade_iii, Cure model
#> 0.852489791
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 91 5.33 1 61 0 1
#> 63 22.77 1 31 1 0
#> 125 15.65 1 67 1 0
#> 106 16.67 1 49 1 0
#> 110 17.56 1 65 0 1
#> 50 10.02 1 NA 1 0
#> 96 14.54 1 33 0 1
#> 154 12.63 1 20 1 0
#> 78 23.88 1 43 0 0
#> 170 19.54 1 43 0 1
#> 69 23.23 1 25 0 1
#> 30 17.43 1 78 0 0
#> 171 16.57 1 41 0 1
#> 6 15.64 1 39 0 0
#> 183 9.24 1 67 1 0
#> 167 15.55 1 56 1 0
#> 25 6.32 1 34 1 0
#> 190 20.81 1 42 1 0
#> 150 20.33 1 48 0 0
#> 36 21.19 1 48 0 1
#> 78.1 23.88 1 43 0 0
#> 100 16.07 1 60 0 0
#> 175 21.91 1 43 0 0
#> 125.1 15.65 1 67 1 0
#> 139 21.49 1 63 1 0
#> 187 9.92 1 39 1 0
#> 59 10.16 1 NA 1 0
#> 100.1 16.07 1 60 0 0
#> 61 10.12 1 36 0 1
#> 194 22.40 1 38 0 1
#> 89 11.44 1 NA 0 0
#> 113 22.86 1 34 0 0
#> 26 15.77 1 49 0 1
#> 195 11.76 1 NA 1 0
#> 51 18.23 1 83 0 1
#> 170.1 19.54 1 43 0 1
#> 6.1 15.64 1 39 0 0
#> 134 17.81 1 47 1 0
#> 59.1 10.16 1 NA 1 0
#> 150.1 20.33 1 48 0 0
#> 100.2 16.07 1 60 0 0
#> 155 13.08 1 26 0 0
#> 129 23.41 1 53 1 0
#> 89.1 11.44 1 NA 0 0
#> 105 19.75 1 60 0 0
#> 10 10.53 1 34 0 0
#> 136 21.83 1 43 0 1
#> 76 19.22 1 54 0 1
#> 167.1 15.55 1 56 1 0
#> 133 14.65 1 57 0 0
#> 101 9.97 1 10 0 1
#> 66 22.13 1 53 0 0
#> 69.1 23.23 1 25 0 1
#> 187.1 9.92 1 39 1 0
#> 187.2 9.92 1 39 1 0
#> 58 19.34 1 39 0 0
#> 93 10.33 1 52 0 1
#> 107 11.18 1 54 1 0
#> 57 14.46 1 45 0 1
#> 68 20.62 1 44 0 0
#> 30.1 17.43 1 78 0 0
#> 69.2 23.23 1 25 0 1
#> 90 20.94 1 50 0 1
#> 30.2 17.43 1 78 0 0
#> 69.3 23.23 1 25 0 1
#> 157 15.10 1 47 0 0
#> 157.1 15.10 1 47 0 0
#> 5 16.43 1 51 0 1
#> 159 10.55 1 50 0 1
#> 49 12.19 1 48 1 0
#> 181 16.46 1 45 0 1
#> 51.1 18.23 1 83 0 1
#> 124 9.73 1 NA 1 0
#> 30.3 17.43 1 78 0 0
#> 81 14.06 1 34 0 0
#> 55 19.34 1 69 0 1
#> 57.1 14.46 1 45 0 1
#> 66.1 22.13 1 53 0 0
#> 168 23.72 1 70 0 0
#> 4 17.64 1 NA 0 1
#> 39 15.59 1 37 0 1
#> 113.1 22.86 1 34 0 0
#> 91.1 5.33 1 61 0 1
#> 79 16.23 1 54 1 0
#> 140 12.68 1 59 1 0
#> 168.1 23.72 1 70 0 0
#> 78.2 23.88 1 43 0 0
#> 45 17.42 1 54 0 1
#> 15 22.68 1 48 0 0
#> 18 15.21 1 49 1 0
#> 179 18.63 1 42 0 0
#> 13 14.34 1 54 0 1
#> 133.1 14.65 1 57 0 0
#> 56 12.21 1 60 0 0
#> 97 19.14 1 65 0 1
#> 190.1 20.81 1 42 1 0
#> 18.1 15.21 1 49 1 0
#> 181.1 16.46 1 45 0 1
#> 154.1 12.63 1 20 1 0
#> 192 16.44 1 31 1 0
#> 124.1 9.73 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 89.2 11.44 1 NA 0 0
#> 106.1 16.67 1 49 1 0
#> 164 23.60 1 76 0 1
#> 136.1 21.83 1 43 0 1
#> 110.1 17.56 1 65 0 1
#> 90.1 20.94 1 50 0 1
#> 61.1 10.12 1 36 0 1
#> 177 12.53 1 75 0 0
#> 194.1 22.40 1 38 0 1
#> 93.1 10.33 1 52 0 1
#> 3 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 47 24.00 0 38 0 1
#> 148 24.00 0 61 1 0
#> 182 24.00 0 35 0 0
#> 20 24.00 0 46 1 0
#> 44 24.00 0 56 0 0
#> 109 24.00 0 48 0 0
#> 53 24.00 0 32 0 1
#> 147 24.00 0 76 1 0
#> 54 24.00 0 53 1 0
#> 138 24.00 0 44 1 0
#> 198 24.00 0 66 0 1
#> 174 24.00 0 49 1 0
#> 112 24.00 0 61 0 0
#> 135 24.00 0 58 1 0
#> 104 24.00 0 50 1 0
#> 46 24.00 0 71 0 0
#> 174.1 24.00 0 49 1 0
#> 95 24.00 0 68 0 1
#> 200 24.00 0 64 0 0
#> 161 24.00 0 45 0 0
#> 9 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 84 24.00 0 39 0 1
#> 28 24.00 0 67 1 0
#> 138.1 24.00 0 44 1 0
#> 46.1 24.00 0 71 0 0
#> 172 24.00 0 41 0 0
#> 148.1 24.00 0 61 1 0
#> 83 24.00 0 6 0 0
#> 135.1 24.00 0 58 1 0
#> 144 24.00 0 28 0 1
#> 73.1 24.00 0 NA 0 1
#> 27 24.00 0 63 1 0
#> 67 24.00 0 25 0 0
#> 122 24.00 0 66 0 0
#> 178 24.00 0 52 1 0
#> 103 24.00 0 56 1 0
#> 84.1 24.00 0 39 0 1
#> 67.1 24.00 0 25 0 0
#> 83.1 24.00 0 6 0 0
#> 109.1 24.00 0 48 0 0
#> 19 24.00 0 57 0 1
#> 160 24.00 0 31 1 0
#> 3.1 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 65 24.00 0 57 1 0
#> 27.1 24.00 0 63 1 0
#> 98 24.00 0 34 1 0
#> 148.2 24.00 0 61 1 0
#> 54.1 24.00 0 53 1 0
#> 95.1 24.00 0 68 0 1
#> 115 24.00 0 NA 1 0
#> 135.2 24.00 0 58 1 0
#> 83.2 24.00 0 6 0 0
#> 112.1 24.00 0 61 0 0
#> 46.2 24.00 0 71 0 0
#> 147.1 24.00 0 76 1 0
#> 22 24.00 0 52 1 0
#> 34 24.00 0 36 0 0
#> 162 24.00 0 51 0 0
#> 144.1 24.00 0 28 0 1
#> 44.1 24.00 0 56 0 0
#> 71 24.00 0 51 0 0
#> 64 24.00 0 43 0 0
#> 160.1 24.00 0 31 1 0
#> 176.1 24.00 0 43 0 1
#> 198.1 24.00 0 66 0 1
#> 19.1 24.00 0 57 0 1
#> 200.1 24.00 0 64 0 0
#> 147.2 24.00 0 76 1 0
#> 80 24.00 0 41 0 0
#> 19.2 24.00 0 57 0 1
#> 3.2 24.00 0 31 1 0
#> 146 24.00 0 63 1 0
#> 35 24.00 0 51 0 0
#> 62 24.00 0 71 0 0
#> 21 24.00 0 47 0 0
#> 186 24.00 0 45 1 0
#> 95.2 24.00 0 68 0 1
#> 148.3 24.00 0 61 1 0
#> 67.2 24.00 0 25 0 0
#> 165 24.00 0 47 0 0
#> 2 24.00 0 9 0 0
#> 151 24.00 0 42 0 0
#> 33 24.00 0 53 0 0
#> 46.3 24.00 0 71 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.0317 NA NA NA
#> 2 age, Cure model 0.00124 NA NA NA
#> 3 grade_ii, Cure model -0.298 NA NA NA
#> 4 grade_iii, Cure model 0.852 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00553 NA NA NA
#> 2 grade_ii, Survival model 0.825 NA NA NA
#> 3 grade_iii, Survival model 0.368 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.031732 0.001237 -0.298338 0.852490
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.7
#> Residual Deviance: 247.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.031731934 0.001237403 -0.298337912 0.852489791
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.005534736 0.824736985 0.367594950
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.9901201 0.3257718 0.7743220 0.6909656 0.6292490 0.8540242 0.8945206
#> [8] 0.0665090 0.5414089 0.2390556 0.6530517 0.7054890 0.7871149 0.9800679
#> [15] 0.8062158 0.9851165 0.4837083 0.5128080 0.4517097 0.0665090 0.7476273
#> [22] 0.4041786 0.7743220 0.4404133 0.9648199 0.7476273 0.9490302 0.3535964
#> [29] 0.2962571 0.7676435 0.6042644 0.5414089 0.7871149 0.6210285 0.5128080
#> [36] 0.7476273 0.8830643 0.2199585 0.5318626 0.9330334 0.4167739 0.5777867
#> [43] 0.8062158 0.8422323 0.9595572 0.3791746 0.2390556 0.9648199 0.9648199
#> [50] 0.5597982 0.9384134 0.9222321 0.8599108 0.5030795 0.6530517 0.2390556
#> [57] 0.4627619 0.6530517 0.2390556 0.8303788 0.8303788 0.7338852 0.9276470
#> [64] 0.9167504 0.7127277 0.6042644 0.6530517 0.8772904 0.5597982 0.8599108
#> [71] 0.3791746 0.1462833 0.7998579 0.2962571 0.9901201 0.7408224 0.8888323
#> [78] 0.1462833 0.0665090 0.6833445 0.3397707 0.8184749 0.5955087 0.8715086
#> [85] 0.8422323 0.9112032 0.5867193 0.4837083 0.8184749 0.7127277 0.8945206
#> [92] 0.7268875 0.6451415 0.6909656 0.1967103 0.4167739 0.6292490 0.4627619
#> [99] 0.9490302 0.9056426 0.3535964 0.9384134 0.0000000 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 91 63 125 106 110 96 154 78 170 69 30 171 6
#> 5.33 22.77 15.65 16.67 17.56 14.54 12.63 23.88 19.54 23.23 17.43 16.57 15.64
#> 183 167 25 190 150 36 78.1 100 175 125.1 139 187 100.1
#> 9.24 15.55 6.32 20.81 20.33 21.19 23.88 16.07 21.91 15.65 21.49 9.92 16.07
#> 61 194 113 26 51 170.1 6.1 134 150.1 100.2 155 129 105
#> 10.12 22.40 22.86 15.77 18.23 19.54 15.64 17.81 20.33 16.07 13.08 23.41 19.75
#> 10 136 76 167.1 133 101 66 69.1 187.1 187.2 58 93 107
#> 10.53 21.83 19.22 15.55 14.65 9.97 22.13 23.23 9.92 9.92 19.34 10.33 11.18
#> 57 68 30.1 69.2 90 30.2 69.3 157 157.1 5 159 49 181
#> 14.46 20.62 17.43 23.23 20.94 17.43 23.23 15.10 15.10 16.43 10.55 12.19 16.46
#> 51.1 30.3 81 55 57.1 66.1 168 39 113.1 91.1 79 140 168.1
#> 18.23 17.43 14.06 19.34 14.46 22.13 23.72 15.59 22.86 5.33 16.23 12.68 23.72
#> 78.2 45 15 18 179 13 133.1 56 97 190.1 18.1 181.1 154.1
#> 23.88 17.42 22.68 15.21 18.63 14.34 14.65 12.21 19.14 20.81 15.21 16.46 12.63
#> 192 111 106.1 164 136.1 110.1 90.1 61.1 177 194.1 93.1 3 72
#> 16.44 17.45 16.67 23.60 21.83 17.56 20.94 10.12 12.53 22.40 10.33 24.00 24.00
#> 47 148 182 20 44 109 53 147 54 138 198 174 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 104 46 174.1 95 200 161 9 84 28 138.1 46.1 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148.1 83 135.1 144 27 67 122 178 103 84.1 67.1 83.1 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 160 3.1 176 65 27.1 98 148.2 54.1 95.1 135.2 83.2 112.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46.2 147.1 22 34 162 144.1 44.1 71 64 160.1 176.1 198.1 19.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200.1 147.2 80 19.2 3.2 146 35 62 21 186 95.2 148.3 67.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 2 151 33 46.3
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[91]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003898201 0.312056754 0.392555326
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.38221260 0.01112188 -0.17818765
#> grade_iii, Cure model
#> 0.35692166
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 139 21.49 1 63 1 0
#> 45 17.42 1 54 0 1
#> 60 13.15 1 38 1 0
#> 188 16.16 1 46 0 1
#> 117 17.46 1 26 0 1
#> 192 16.44 1 31 1 0
#> 113 22.86 1 34 0 0
#> 139.1 21.49 1 63 1 0
#> 192.1 16.44 1 31 1 0
#> 93 10.33 1 52 0 1
#> 89 11.44 1 NA 0 0
#> 41 18.02 1 40 1 0
#> 88 18.37 1 47 0 0
#> 166 19.98 1 48 0 0
#> 97 19.14 1 65 0 1
#> 42 12.43 1 49 0 1
#> 70 7.38 1 30 1 0
#> 32 20.90 1 37 1 0
#> 127 3.53 1 62 0 1
#> 188.1 16.16 1 46 0 1
#> 133 14.65 1 57 0 0
#> 100 16.07 1 60 0 0
#> 16 8.71 1 71 0 1
#> 85 16.44 1 36 0 0
#> 157 15.10 1 47 0 0
#> 25 6.32 1 34 1 0
#> 16.1 8.71 1 71 0 1
#> 58 19.34 1 39 0 0
#> 81 14.06 1 34 0 0
#> 79 16.23 1 54 1 0
#> 93.1 10.33 1 52 0 1
#> 93.2 10.33 1 52 0 1
#> 136 21.83 1 43 0 1
#> 30 17.43 1 78 0 0
#> 189 10.51 1 NA 1 0
#> 123 13.00 1 44 1 0
#> 168 23.72 1 70 0 0
#> 26 15.77 1 49 0 1
#> 79.1 16.23 1 54 1 0
#> 39 15.59 1 37 0 1
#> 134 17.81 1 47 1 0
#> 63 22.77 1 31 1 0
#> 177 12.53 1 75 0 0
#> 85.1 16.44 1 36 0 0
#> 167 15.55 1 56 1 0
#> 145 10.07 1 65 1 0
#> 133.1 14.65 1 57 0 0
#> 129 23.41 1 53 1 0
#> 179 18.63 1 42 0 0
#> 180 14.82 1 37 0 0
#> 101 9.97 1 10 0 1
#> 145.1 10.07 1 65 1 0
#> 37 12.52 1 57 1 0
#> 117.1 17.46 1 26 0 1
#> 158 20.14 1 74 1 0
#> 61 10.12 1 36 0 1
#> 24 23.89 1 38 0 0
#> 86 23.81 1 58 0 1
#> 197 21.60 1 69 1 0
#> 52 10.42 1 52 0 1
#> 77 7.27 1 67 0 1
#> 154 12.63 1 20 1 0
#> 123.1 13.00 1 44 1 0
#> 134.1 17.81 1 47 1 0
#> 179.1 18.63 1 42 0 0
#> 32.1 20.90 1 37 1 0
#> 128 20.35 1 35 0 1
#> 194 22.40 1 38 0 1
#> 110 17.56 1 65 0 1
#> 55 19.34 1 69 0 1
#> 170 19.54 1 43 0 1
#> 113.1 22.86 1 34 0 0
#> 4 17.64 1 NA 0 1
#> 110.1 17.56 1 65 0 1
#> 81.1 14.06 1 34 0 0
#> 177.1 12.53 1 75 0 0
#> 91 5.33 1 61 0 1
#> 106 16.67 1 49 1 0
#> 150 20.33 1 48 0 0
#> 114 13.68 1 NA 0 0
#> 124 9.73 1 NA 1 0
#> 26.1 15.77 1 49 0 1
#> 8 18.43 1 32 0 0
#> 170.1 19.54 1 43 0 1
#> 179.2 18.63 1 42 0 0
#> 190 20.81 1 42 1 0
#> 14 12.89 1 21 0 0
#> 134.2 17.81 1 47 1 0
#> 179.3 18.63 1 42 0 0
#> 106.1 16.67 1 49 1 0
#> 192.2 16.44 1 31 1 0
#> 86.1 23.81 1 58 0 1
#> 158.1 20.14 1 74 1 0
#> 113.2 22.86 1 34 0 0
#> 10 10.53 1 34 0 0
#> 177.2 12.53 1 75 0 0
#> 96 14.54 1 33 0 1
#> 5 16.43 1 51 0 1
#> 13 14.34 1 54 0 1
#> 78 23.88 1 43 0 0
#> 169 22.41 1 46 0 0
#> 188.2 16.16 1 46 0 1
#> 190.1 20.81 1 42 1 0
#> 97.1 19.14 1 65 0 1
#> 164 23.60 1 76 0 1
#> 40 18.00 1 28 1 0
#> 23 16.92 1 61 0 0
#> 110.2 17.56 1 65 0 1
#> 195 11.76 1 NA 1 0
#> 169.1 22.41 1 46 0 0
#> 136.1 21.83 1 43 0 1
#> 14.1 12.89 1 21 0 0
#> 35 24.00 0 51 0 0
#> 104 24.00 0 50 1 0
#> 20 24.00 0 46 1 0
#> 120 24.00 0 68 0 1
#> 84 24.00 0 39 0 1
#> 185 24.00 0 44 1 0
#> 2 24.00 0 9 0 0
#> 151 24.00 0 42 0 0
#> 142 24.00 0 53 0 0
#> 98 24.00 0 34 1 0
#> 156 24.00 0 50 1 0
#> 80 24.00 0 41 0 0
#> 121 24.00 0 57 1 0
#> 193 24.00 0 45 0 1
#> 48 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 109 24.00 0 48 0 0
#> 7 24.00 0 37 1 0
#> 126 24.00 0 48 0 0
#> 75 24.00 0 21 1 0
#> 141 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 191 24.00 0 60 0 1
#> 17 24.00 0 38 0 1
#> 120.1 24.00 0 68 0 1
#> 33 24.00 0 53 0 0
#> 46 24.00 0 71 0 0
#> 120.2 24.00 0 68 0 1
#> 48.1 24.00 0 31 1 0
#> 120.3 24.00 0 68 0 1
#> 65.1 24.00 0 57 1 0
#> 186 24.00 0 45 1 0
#> 116 24.00 0 58 0 1
#> 35.1 24.00 0 51 0 0
#> 11 24.00 0 42 0 1
#> 67 24.00 0 25 0 0
#> 126.1 24.00 0 48 0 0
#> 151.1 24.00 0 42 0 0
#> 104.1 24.00 0 50 1 0
#> 146 24.00 0 63 1 0
#> 176 24.00 0 43 0 1
#> 53 24.00 0 32 0 1
#> 121.1 24.00 0 57 1 0
#> 28 24.00 0 67 1 0
#> 151.2 24.00 0 42 0 0
#> 65.2 24.00 0 57 1 0
#> 38 24.00 0 31 1 0
#> 151.3 24.00 0 42 0 0
#> 80.1 24.00 0 41 0 0
#> 84.1 24.00 0 39 0 1
#> 191.1 24.00 0 60 0 1
#> 173 24.00 0 19 0 1
#> 83 24.00 0 6 0 0
#> 11.1 24.00 0 42 0 1
#> 22 24.00 0 52 1 0
#> 95 24.00 0 68 0 1
#> 48.2 24.00 0 31 1 0
#> 35.2 24.00 0 51 0 0
#> 95.1 24.00 0 68 0 1
#> 165 24.00 0 47 0 0
#> 7.1 24.00 0 37 1 0
#> 1 24.00 0 23 1 0
#> 151.4 24.00 0 42 0 0
#> 7.2 24.00 0 37 1 0
#> 1.1 24.00 0 23 1 0
#> 17.1 24.00 0 38 0 1
#> 173.1 24.00 0 19 0 1
#> 21.1 24.00 0 47 0 0
#> 9 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 44 24.00 0 56 0 0
#> 172 24.00 0 41 0 0
#> 7.3 24.00 0 37 1 0
#> 186.1 24.00 0 45 1 0
#> 138 24.00 0 44 1 0
#> 156.1 24.00 0 50 1 0
#> 143 24.00 0 51 0 0
#> 17.2 24.00 0 38 0 1
#> 172.1 24.00 0 41 0 0
#> 9.1 24.00 0 31 1 0
#> 109.1 24.00 0 48 0 0
#> 118 24.00 0 44 1 0
#> 176.1 24.00 0 43 0 1
#> 126.2 24.00 0 48 0 0
#> 148 24.00 0 61 1 0
#> 138.1 24.00 0 44 1 0
#> 12 24.00 0 63 0 0
#> 200 24.00 0 64 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.382 NA NA NA
#> 2 age, Cure model 0.0111 NA NA NA
#> 3 grade_ii, Cure model -0.178 NA NA NA
#> 4 grade_iii, Cure model 0.357 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00390 NA NA NA
#> 2 grade_ii, Survival model 0.312 NA NA NA
#> 3 grade_iii, Survival model 0.393 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.38221 0.01112 -0.17819 0.35692
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 267.3
#> Residual Deviance: 263.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.38221260 0.01112188 -0.17818765 0.35692166
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003898201 0.312056754 0.392555326
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.184007677 0.507062204 0.759861642 0.616167979 0.479299901 0.544152561
#> [7] 0.081556152 0.184007677 0.544152561 0.876390848 0.404301207 0.394584067
#> [13] 0.281238271 0.328943727 0.849378270 0.956014252 0.203864304 0.991229396
#> [19] 0.616167979 0.705905462 0.642942283 0.938414075 0.544152561 0.687901137
#> [25] 0.973649717 0.938414075 0.309987176 0.741920275 0.597997706 0.876390848
#> [31] 0.876390848 0.153699766 0.497719716 0.768866864 0.048607551 0.652020541
#> [37] 0.597997706 0.669940051 0.423606288 0.111217479 0.813544222 0.544152561
#> [43] 0.678926432 0.911840582 0.705905462 0.070761921 0.347738883 0.696895489
#> [49] 0.929551839 0.911840582 0.840354031 0.479299901 0.262095052 0.902931025
#> [55] 0.005192713 0.029737392 0.173718657 0.867395772 0.964837641 0.804583339
#> [61] 0.768866864 0.423606288 0.347738883 0.203864304 0.242619012 0.142978984
#> [67] 0.451580985 0.309987176 0.291036489 0.081556152 0.451580985 0.741920275
#> [73] 0.813544222 0.982446138 0.525714352 0.252324946 0.652020541 0.384906833
#> [79] 0.291036489 0.347738883 0.223375429 0.786709161 0.423606288 0.347738883
#> [85] 0.525714352 0.544152561 0.029737392 0.262095052 0.081556152 0.858381152
#> [91] 0.813544222 0.723901371 0.588812447 0.732921879 0.016558870 0.121922085
#> [97] 0.616167979 0.223375429 0.328943727 0.059785178 0.413979056 0.516370453
#> [103] 0.451580985 0.121922085 0.153699766 0.786709161 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000 0.000000000
#>
#> $Time
#> 139 45 60 188 117 192 113 139.1 192.1 93 41 88 166
#> 21.49 17.42 13.15 16.16 17.46 16.44 22.86 21.49 16.44 10.33 18.02 18.37 19.98
#> 97 42 70 32 127 188.1 133 100 16 85 157 25 16.1
#> 19.14 12.43 7.38 20.90 3.53 16.16 14.65 16.07 8.71 16.44 15.10 6.32 8.71
#> 58 81 79 93.1 93.2 136 30 123 168 26 79.1 39 134
#> 19.34 14.06 16.23 10.33 10.33 21.83 17.43 13.00 23.72 15.77 16.23 15.59 17.81
#> 63 177 85.1 167 145 133.1 129 179 180 101 145.1 37 117.1
#> 22.77 12.53 16.44 15.55 10.07 14.65 23.41 18.63 14.82 9.97 10.07 12.52 17.46
#> 158 61 24 86 197 52 77 154 123.1 134.1 179.1 32.1 128
#> 20.14 10.12 23.89 23.81 21.60 10.42 7.27 12.63 13.00 17.81 18.63 20.90 20.35
#> 194 110 55 170 113.1 110.1 81.1 177.1 91 106 150 26.1 8
#> 22.40 17.56 19.34 19.54 22.86 17.56 14.06 12.53 5.33 16.67 20.33 15.77 18.43
#> 170.1 179.2 190 14 134.2 179.3 106.1 192.2 86.1 158.1 113.2 10 177.2
#> 19.54 18.63 20.81 12.89 17.81 18.63 16.67 16.44 23.81 20.14 22.86 10.53 12.53
#> 96 5 13 78 169 188.2 190.1 97.1 164 40 23 110.2 169.1
#> 14.54 16.43 14.34 23.88 22.41 16.16 20.81 19.14 23.60 18.00 16.92 17.56 22.41
#> 136.1 14.1 35 104 20 120 84 185 2 151 142 98 156
#> 21.83 12.89 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 121 193 48 21 109 7 126 75 141 65 191 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120.1 33 46 120.2 48.1 120.3 65.1 186 116 35.1 11 67 126.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151.1 104.1 146 176 53 121.1 28 151.2 65.2 38 151.3 80.1 84.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191.1 173 83 11.1 22 95 48.2 35.2 95.1 165 7.1 1 151.4
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7.2 1.1 17.1 173.1 21.1 9 19 44 172 7.3 186.1 138 156.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 17.2 172.1 9.1 109.1 118 176.1 126.2 148 138.1 12 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[92]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.002371799 0.252193437 0.251591742
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.80147136 0.02206024 -0.18675475
#> grade_iii, Cure model
#> 0.07596870
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 70 7.38 1 30 1 0
#> 177 12.53 1 75 0 0
#> 30 17.43 1 78 0 0
#> 86 23.81 1 58 0 1
#> 124 9.73 1 NA 1 0
#> 129 23.41 1 53 1 0
#> 113 22.86 1 34 0 0
#> 169 22.41 1 46 0 0
#> 81 14.06 1 34 0 0
#> 175 21.91 1 43 0 0
#> 157 15.10 1 47 0 0
#> 127 3.53 1 62 0 1
#> 111 17.45 1 47 0 1
#> 166 19.98 1 48 0 0
#> 125 15.65 1 67 1 0
#> 89 11.44 1 NA 0 0
#> 133 14.65 1 57 0 0
#> 24 23.89 1 38 0 0
#> 24.1 23.89 1 38 0 0
#> 6 15.64 1 39 0 0
#> 45 17.42 1 54 0 1
#> 153 21.33 1 55 1 0
#> 197 21.60 1 69 1 0
#> 171 16.57 1 41 0 1
#> 194 22.40 1 38 0 1
#> 23 16.92 1 61 0 0
#> 155 13.08 1 26 0 0
#> 179 18.63 1 42 0 0
#> 42 12.43 1 49 0 1
#> 8 18.43 1 32 0 0
#> 155.1 13.08 1 26 0 0
#> 145 10.07 1 65 1 0
#> 192 16.44 1 31 1 0
#> 42.1 12.43 1 49 0 1
#> 179.1 18.63 1 42 0 0
#> 133.1 14.65 1 57 0 0
#> 81.1 14.06 1 34 0 0
#> 179.2 18.63 1 42 0 0
#> 197.1 21.60 1 69 1 0
#> 150 20.33 1 48 0 0
#> 14 12.89 1 21 0 0
#> 190 20.81 1 42 1 0
#> 77 7.27 1 67 0 1
#> 25 6.32 1 34 1 0
#> 76 19.22 1 54 0 1
#> 194.1 22.40 1 38 0 1
#> 52 10.42 1 52 0 1
#> 79 16.23 1 54 1 0
#> 37 12.52 1 57 1 0
#> 139 21.49 1 63 1 0
#> 145.1 10.07 1 65 1 0
#> 130 16.47 1 53 0 1
#> 13 14.34 1 54 0 1
#> 91 5.33 1 61 0 1
#> 190.1 20.81 1 42 1 0
#> 124.1 9.73 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 159 10.55 1 50 0 1
#> 189 10.51 1 NA 1 0
#> 133.2 14.65 1 57 0 0
#> 29 15.45 1 68 1 0
#> 78 23.88 1 43 0 0
#> 92 22.92 1 47 0 1
#> 189.1 10.51 1 NA 1 0
#> 41 18.02 1 40 1 0
#> 180 14.82 1 37 0 0
#> 32 20.90 1 37 1 0
#> 194.2 22.40 1 38 0 1
#> 79.1 16.23 1 54 1 0
#> 158 20.14 1 74 1 0
#> 139.1 21.49 1 63 1 0
#> 175.1 21.91 1 43 0 0
#> 51 18.23 1 83 0 1
#> 29.1 15.45 1 68 1 0
#> 60 13.15 1 38 1 0
#> 184 17.77 1 38 0 0
#> 179.3 18.63 1 42 0 0
#> 111.1 17.45 1 47 0 1
#> 37.1 12.52 1 57 1 0
#> 43 12.10 1 61 0 1
#> 63 22.77 1 31 1 0
#> 190.2 20.81 1 42 1 0
#> 168.1 23.72 1 70 0 0
#> 188 16.16 1 46 0 1
#> 37.2 12.52 1 57 1 0
#> 96 14.54 1 33 0 1
#> 105 19.75 1 60 0 0
#> 134 17.81 1 47 1 0
#> 177.1 12.53 1 75 0 0
#> 168.2 23.72 1 70 0 0
#> 68 20.62 1 44 0 0
#> 10 10.53 1 34 0 0
#> 32.1 20.90 1 37 1 0
#> 97 19.14 1 65 0 1
#> 81.2 14.06 1 34 0 0
#> 153.1 21.33 1 55 1 0
#> 100 16.07 1 60 0 0
#> 14.1 12.89 1 21 0 0
#> 128 20.35 1 35 0 1
#> 81.3 14.06 1 34 0 0
#> 133.3 14.65 1 57 0 0
#> 140 12.68 1 59 1 0
#> 13.1 14.34 1 54 0 1
#> 18 15.21 1 49 1 0
#> 29.2 15.45 1 68 1 0
#> 199 19.81 1 NA 0 1
#> 180.1 14.82 1 37 0 0
#> 85 16.44 1 36 0 0
#> 150.1 20.33 1 48 0 0
#> 194.3 22.40 1 38 0 1
#> 194.4 22.40 1 38 0 1
#> 93 10.33 1 52 0 1
#> 119 24.00 0 17 0 0
#> 21 24.00 0 47 0 0
#> 172 24.00 0 41 0 0
#> 137 24.00 0 45 1 0
#> 62 24.00 0 71 0 0
#> 17 24.00 0 38 0 1
#> 112 24.00 0 61 0 0
#> 44 24.00 0 56 0 0
#> 144 24.00 0 28 0 1
#> 162 24.00 0 51 0 0
#> 46 24.00 0 71 0 0
#> 2 24.00 0 9 0 0
#> 65 24.00 0 57 1 0
#> 174 24.00 0 49 1 0
#> 53 24.00 0 32 0 1
#> 138 24.00 0 44 1 0
#> 75 24.00 0 21 1 0
#> 103 24.00 0 56 1 0
#> 193 24.00 0 45 0 1
#> 120 24.00 0 68 0 1
#> 46.1 24.00 0 71 0 0
#> 172.1 24.00 0 41 0 0
#> 1 24.00 0 23 1 0
#> 17.1 24.00 0 38 0 1
#> 160 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 54 24.00 0 53 1 0
#> 178 24.00 0 52 1 0
#> 137.1 24.00 0 45 1 0
#> 64 24.00 0 43 0 0
#> 20 24.00 0 46 1 0
#> 172.2 24.00 0 41 0 0
#> 151 24.00 0 42 0 0
#> 198 24.00 0 66 0 1
#> 132 24.00 0 55 0 0
#> 9 24.00 0 31 1 0
#> 116 24.00 0 58 0 1
#> 144.1 24.00 0 28 0 1
#> 163 24.00 0 66 0 0
#> 137.2 24.00 0 45 1 0
#> 112.1 24.00 0 61 0 0
#> 156 24.00 0 50 1 0
#> 151.1 24.00 0 42 0 0
#> 54.1 24.00 0 53 1 0
#> 135 24.00 0 58 1 0
#> 80 24.00 0 41 0 0
#> 38 24.00 0 31 1 0
#> 119.1 24.00 0 17 0 0
#> 80.1 24.00 0 41 0 0
#> 54.2 24.00 0 53 1 0
#> 120.1 24.00 0 68 0 1
#> 131 24.00 0 66 0 0
#> 98 24.00 0 34 1 0
#> 112.2 24.00 0 61 0 0
#> 193.1 24.00 0 45 0 1
#> 193.2 24.00 0 45 0 1
#> 94 24.00 0 51 0 1
#> 33 24.00 0 53 0 0
#> 3 24.00 0 31 1 0
#> 172.3 24.00 0 41 0 0
#> 176 24.00 0 43 0 1
#> 191 24.00 0 60 0 1
#> 173 24.00 0 19 0 1
#> 186 24.00 0 45 1 0
#> 126 24.00 0 48 0 0
#> 9.1 24.00 0 31 1 0
#> 126.1 24.00 0 48 0 0
#> 151.2 24.00 0 42 0 0
#> 146 24.00 0 63 1 0
#> 84 24.00 0 39 0 1
#> 142 24.00 0 53 0 0
#> 104 24.00 0 50 1 0
#> 22 24.00 0 52 1 0
#> 2.1 24.00 0 9 0 0
#> 162.1 24.00 0 51 0 0
#> 28 24.00 0 67 1 0
#> 119.2 24.00 0 17 0 0
#> 27 24.00 0 63 1 0
#> 53.1 24.00 0 32 0 1
#> 174.1 24.00 0 49 1 0
#> 73 24.00 0 NA 0 1
#> 182 24.00 0 35 0 0
#> 152 24.00 0 36 0 1
#> 191.1 24.00 0 60 0 1
#> 144.2 24.00 0 28 0 1
#> 102 24.00 0 49 0 0
#> 48 24.00 0 31 1 0
#> 35 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.801 NA NA NA
#> 2 age, Cure model 0.0221 NA NA NA
#> 3 grade_ii, Cure model -0.187 NA NA NA
#> 4 grade_iii, Cure model 0.0760 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00237 NA NA NA
#> 2 grade_ii, Survival model 0.252 NA NA NA
#> 3 grade_iii, Survival model 0.252 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.80147 0.02206 -0.18675 0.07597
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.7
#> Residual Deviance: 260.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.80147136 0.02206024 -0.18675475 0.07596870
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.002371799 0.252193437 0.251591742
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.96398381 0.86035569 0.56716080 0.07612797 0.13467171 0.16310064
#> [7] 0.19033903 0.78420460 0.25606313 0.70655725 0.99284622 0.55009903
#> [13] 0.43452962 0.65881763 0.73015676 0.02253802 0.02253802 0.66693406
#> [19] 0.57573043 0.32021043 0.27827135 0.59273345 0.20364907 0.58424157
#> [25] 0.82224417 0.47117909 0.89779002 0.50605933 0.82224417 0.94949085
#> [31] 0.60956227 0.89779002 0.47117909 0.73015676 0.78420460 0.47117909
#> [37] 0.27827135 0.40669778 0.83749667 0.35976119 0.97123684 0.97846248
#> [43] 0.45299962 0.20364907 0.93480351 0.62611450 0.87547763 0.29960303
#> [49] 0.94949085 0.60117485 0.76881997 0.98566711 0.35976119 0.09387678
#> [55] 0.92003233 0.73015676 0.67504093 0.05620566 0.14918173 0.52385729
#> [61] 0.71446347 0.34021824 0.20364907 0.62611450 0.42525613 0.29960303
#> [67] 0.25606313 0.51500181 0.67504093 0.81457313 0.54138169 0.47117909
#> [73] 0.55009903 0.87547763 0.91261759 0.17692126 0.35976119 0.09387678
#> [79] 0.64246674 0.87547763 0.76101631 0.44377931 0.53265110 0.86035569
#> [85] 0.09387678 0.38772783 0.92742039 0.34021824 0.46213409 0.78420460
#> [91] 0.32021043 0.65065004 0.83749667 0.39725779 0.78420460 0.73015676
#> [97] 0.85273501 0.76881997 0.69864059 0.67504093 0.71446347 0.60956227
#> [103] 0.40669778 0.20364907 0.20364907 0.94216020 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000
#>
#> $Time
#> 70 177 30 86 129 113 169 81 175 157 127 111 166
#> 7.38 12.53 17.43 23.81 23.41 22.86 22.41 14.06 21.91 15.10 3.53 17.45 19.98
#> 125 133 24 24.1 6 45 153 197 171 194 23 155 179
#> 15.65 14.65 23.89 23.89 15.64 17.42 21.33 21.60 16.57 22.40 16.92 13.08 18.63
#> 42 8 155.1 145 192 42.1 179.1 133.1 81.1 179.2 197.1 150 14
#> 12.43 18.43 13.08 10.07 16.44 12.43 18.63 14.65 14.06 18.63 21.60 20.33 12.89
#> 190 77 25 76 194.1 52 79 37 139 145.1 130 13 91
#> 20.81 7.27 6.32 19.22 22.40 10.42 16.23 12.52 21.49 10.07 16.47 14.34 5.33
#> 190.1 168 159 133.2 29 78 92 41 180 32 194.2 79.1 158
#> 20.81 23.72 10.55 14.65 15.45 23.88 22.92 18.02 14.82 20.90 22.40 16.23 20.14
#> 139.1 175.1 51 29.1 60 184 179.3 111.1 37.1 43 63 190.2 168.1
#> 21.49 21.91 18.23 15.45 13.15 17.77 18.63 17.45 12.52 12.10 22.77 20.81 23.72
#> 188 37.2 96 105 134 177.1 168.2 68 10 32.1 97 81.2 153.1
#> 16.16 12.52 14.54 19.75 17.81 12.53 23.72 20.62 10.53 20.90 19.14 14.06 21.33
#> 100 14.1 128 81.3 133.3 140 13.1 18 29.2 180.1 85 150.1 194.3
#> 16.07 12.89 20.35 14.06 14.65 12.68 14.34 15.21 15.45 14.82 16.44 20.33 22.40
#> 194.4 93 119 21 172 137 62 17 112 44 144 162 46
#> 22.40 10.33 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 65 174 53 138 75 103 193 120 46.1 172.1 1 17.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160 87 54 178 137.1 64 20 172.2 151 198 132 9 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144.1 163 137.2 112.1 156 151.1 54.1 135 80 38 119.1 80.1 54.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120.1 131 98 112.2 193.1 193.2 94 33 3 172.3 176 191 173
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 126 9.1 126.1 151.2 146 84 142 104 22 2.1 162.1 28
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119.2 27 53.1 174.1 182 152 191.1 144.2 102 48 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[93]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.008275025 1.582790871 0.748180540
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.496209886 0.009982384 -0.368780779
#> grade_iii, Cure model
#> 0.830101104
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 167 15.55 1 56 1 0
#> 70 7.38 1 30 1 0
#> 8 18.43 1 32 0 0
#> 60 13.15 1 38 1 0
#> 92 22.92 1 47 0 1
#> 66 22.13 1 53 0 0
#> 127 3.53 1 62 0 1
#> 149 8.37 1 33 1 0
#> 43 12.10 1 61 0 1
#> 92.1 22.92 1 47 0 1
#> 128 20.35 1 35 0 1
#> 189 10.51 1 NA 1 0
#> 133 14.65 1 57 0 0
#> 43.1 12.10 1 61 0 1
#> 24 23.89 1 38 0 0
#> 166 19.98 1 48 0 0
#> 66.1 22.13 1 53 0 0
#> 66.2 22.13 1 53 0 0
#> 125 15.65 1 67 1 0
#> 153 21.33 1 55 1 0
#> 70.1 7.38 1 30 1 0
#> 68 20.62 1 44 0 0
#> 13 14.34 1 54 0 1
#> 159 10.55 1 50 0 1
#> 101 9.97 1 10 0 1
#> 90 20.94 1 50 0 1
#> 59 10.16 1 NA 1 0
#> 89 11.44 1 NA 0 0
#> 18 15.21 1 49 1 0
#> 59.1 10.16 1 NA 1 0
#> 76 19.22 1 54 0 1
#> 194 22.40 1 38 0 1
#> 113 22.86 1 34 0 0
#> 195 11.76 1 NA 1 0
#> 187 9.92 1 39 1 0
#> 6 15.64 1 39 0 0
#> 66.3 22.13 1 53 0 0
#> 164 23.60 1 76 0 1
#> 77 7.27 1 67 0 1
#> 105 19.75 1 60 0 0
#> 117 17.46 1 26 0 1
#> 4 17.64 1 NA 0 1
#> 43.2 12.10 1 61 0 1
#> 175 21.91 1 43 0 0
#> 199 19.81 1 NA 0 1
#> 42 12.43 1 49 0 1
#> 29 15.45 1 68 1 0
#> 168 23.72 1 70 0 0
#> 159.1 10.55 1 50 0 1
#> 125.1 15.65 1 67 1 0
#> 24.1 23.89 1 38 0 0
#> 195.1 11.76 1 NA 1 0
#> 57 14.46 1 45 0 1
#> 89.1 11.44 1 NA 0 0
#> 113.1 22.86 1 34 0 0
#> 52 10.42 1 52 0 1
#> 39 15.59 1 37 0 1
#> 41 18.02 1 40 1 0
#> 168.1 23.72 1 70 0 0
#> 51 18.23 1 83 0 1
#> 43.3 12.10 1 61 0 1
#> 107 11.18 1 54 1 0
#> 81 14.06 1 34 0 0
#> 24.2 23.89 1 38 0 0
#> 107.1 11.18 1 54 1 0
#> 43.4 12.10 1 61 0 1
#> 4.1 17.64 1 NA 0 1
#> 92.2 22.92 1 47 0 1
#> 100 16.07 1 60 0 0
#> 136 21.83 1 43 0 1
#> 85 16.44 1 36 0 0
#> 60.1 13.15 1 38 1 0
#> 130 16.47 1 53 0 1
#> 24.3 23.89 1 38 0 0
#> 58 19.34 1 39 0 0
#> 92.3 22.92 1 47 0 1
#> 15 22.68 1 48 0 0
#> 25 6.32 1 34 1 0
#> 93 10.33 1 52 0 1
#> 52.1 10.42 1 52 0 1
#> 56 12.21 1 60 0 0
#> 108 18.29 1 39 0 1
#> 90.1 20.94 1 50 0 1
#> 128.1 20.35 1 35 0 1
#> 117.1 17.46 1 26 0 1
#> 145 10.07 1 65 1 0
#> 164.1 23.60 1 76 0 1
#> 150 20.33 1 48 0 0
#> 96 14.54 1 33 0 1
#> 184 17.77 1 38 0 0
#> 16 8.71 1 71 0 1
#> 164.2 23.60 1 76 0 1
#> 56.1 12.21 1 60 0 0
#> 114 13.68 1 NA 0 0
#> 113.2 22.86 1 34 0 0
#> 192 16.44 1 31 1 0
#> 24.4 23.89 1 38 0 0
#> 189.1 10.51 1 NA 1 0
#> 52.2 10.42 1 52 0 1
#> 189.2 10.51 1 NA 1 0
#> 180 14.82 1 37 0 0
#> 154 12.63 1 20 1 0
#> 58.1 19.34 1 39 0 0
#> 170 19.54 1 43 0 1
#> 117.2 17.46 1 26 0 1
#> 23 16.92 1 61 0 0
#> 88 18.37 1 47 0 0
#> 110 17.56 1 65 0 1
#> 170.1 19.54 1 43 0 1
#> 169 22.41 1 46 0 0
#> 139 21.49 1 63 1 0
#> 23.1 16.92 1 61 0 0
#> 82 24.00 0 34 0 0
#> 142 24.00 0 53 0 0
#> 27 24.00 0 63 1 0
#> 67 24.00 0 25 0 0
#> 72 24.00 0 40 0 1
#> 46 24.00 0 71 0 0
#> 186 24.00 0 45 1 0
#> 74 24.00 0 43 0 1
#> 146 24.00 0 63 1 0
#> 44 24.00 0 56 0 0
#> 146.1 24.00 0 63 1 0
#> 80 24.00 0 41 0 0
#> 54 24.00 0 53 1 0
#> 73 24.00 0 NA 0 1
#> 196 24.00 0 19 0 0
#> 120 24.00 0 68 0 1
#> 104 24.00 0 50 1 0
#> 2 24.00 0 9 0 0
#> 2.1 24.00 0 9 0 0
#> 48 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 44.1 24.00 0 56 0 0
#> 103 24.00 0 56 1 0
#> 44.2 24.00 0 56 0 0
#> 116 24.00 0 58 0 1
#> 19 24.00 0 57 0 1
#> 165 24.00 0 47 0 0
#> 148 24.00 0 61 1 0
#> 109 24.00 0 48 0 0
#> 141 24.00 0 44 1 0
#> 147 24.00 0 76 1 0
#> 176 24.00 0 43 0 1
#> 9 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 156 24.00 0 50 1 0
#> 147.1 24.00 0 76 1 0
#> 182 24.00 0 35 0 0
#> 34 24.00 0 36 0 0
#> 126 24.00 0 48 0 0
#> 9.1 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 48.1 24.00 0 31 1 0
#> 17 24.00 0 38 0 1
#> 193 24.00 0 45 0 1
#> 83 24.00 0 6 0 0
#> 131 24.00 0 66 0 0
#> 34.1 24.00 0 36 0 0
#> 95 24.00 0 68 0 1
#> 119 24.00 0 17 0 0
#> 131.1 24.00 0 66 0 0
#> 173 24.00 0 19 0 1
#> 131.2 24.00 0 66 0 0
#> 196.1 24.00 0 19 0 0
#> 173.1 24.00 0 19 0 1
#> 2.2 24.00 0 9 0 0
#> 34.2 24.00 0 36 0 0
#> 148.1 24.00 0 61 1 0
#> 146.2 24.00 0 63 1 0
#> 9.2 24.00 0 31 1 0
#> 46.1 24.00 0 71 0 0
#> 151 24.00 0 42 0 0
#> 11 24.00 0 42 0 1
#> 178 24.00 0 52 1 0
#> 17.1 24.00 0 38 0 1
#> 165.1 24.00 0 47 0 0
#> 94 24.00 0 51 0 1
#> 82.1 24.00 0 34 0 0
#> 131.3 24.00 0 66 0 0
#> 191.1 24.00 0 60 0 1
#> 126.1 24.00 0 48 0 0
#> 165.2 24.00 0 47 0 0
#> 28 24.00 0 67 1 0
#> 54.1 24.00 0 53 1 0
#> 131.4 24.00 0 66 0 0
#> 20 24.00 0 46 1 0
#> 102 24.00 0 49 0 0
#> 142.1 24.00 0 53 0 0
#> 1.1 24.00 0 23 1 0
#> 112 24.00 0 61 0 0
#> 28.1 24.00 0 67 1 0
#> 2.3 24.00 0 9 0 0
#> 27.1 24.00 0 63 1 0
#> 73.1 24.00 0 NA 0 1
#> 34.3 24.00 0 36 0 0
#> 3 24.00 0 31 1 0
#> 72.1 24.00 0 40 0 1
#> 147.2 24.00 0 76 1 0
#> 17.2 24.00 0 38 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.496 NA NA NA
#> 2 age, Cure model 0.00998 NA NA NA
#> 3 grade_ii, Cure model -0.369 NA NA NA
#> 4 grade_iii, Cure model 0.830 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00828 NA NA NA
#> 2 grade_ii, Survival model 1.58 NA NA NA
#> 3 grade_iii, Survival model 0.748 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.496210 0.009982 -0.368781 0.830101
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 255.6
#> Residual Deviance: 244.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.496209886 0.009982384 -0.368780779 0.830101104
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.008275025 1.582790871 0.748180540
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.70528186 0.96675663 0.49983272 0.78443363 0.13226359 0.25161463
#> [7] 0.99342708 0.95977085 0.83253189 0.13226359 0.38845186 0.74090269
#> [13] 0.83253189 0.01530405 0.42157929 0.25161463 0.25161463 0.66756658
#> [19] 0.34280005 0.96675663 0.37695074 0.76710973 0.88628185 0.93823537
#> [25] 0.35450518 0.72342355 0.48863877 0.23874297 0.17643758 0.94550939
#> [31] 0.68635865 0.25161463 0.09153967 0.98013849 0.43288690 0.57680583
#> [37] 0.83253189 0.30274275 0.80872175 0.71445481 0.06019711 0.88628185
#> [43] 0.66756658 0.01530405 0.75842521 0.17643758 0.90127801 0.69585600
#> [49] 0.54481168 0.06019711 0.53362241 0.83253189 0.87118425 0.77575982
#> [55] 0.01530405 0.87118425 0.83253189 0.13226359 0.65759566 0.31661239
#> [61] 0.63792087 0.78443363 0.62760411 0.01530405 0.46632970 0.13226359
#> [67] 0.21246633 0.98684260 0.92347203 0.90127801 0.81664406 0.52241830
#> [73] 0.35450518 0.38845186 0.57680583 0.93090764 0.09153967 0.41037024
#> [79] 0.74969508 0.55545522 0.95264477 0.09153967 0.81664406 0.17643758
#> [85] 0.63792087 0.01530405 0.90127801 0.73214936 0.80076758 0.46632970
#> [91] 0.44431131 0.57680583 0.60701842 0.51108530 0.56615408 0.44431131
#> [97] 0.22548341 0.33019626 0.60701842 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 167 70 8 60 92 66 127 149 43 92.1 128 133 43.1
#> 15.55 7.38 18.43 13.15 22.92 22.13 3.53 8.37 12.10 22.92 20.35 14.65 12.10
#> 24 166 66.1 66.2 125 153 70.1 68 13 159 101 90 18
#> 23.89 19.98 22.13 22.13 15.65 21.33 7.38 20.62 14.34 10.55 9.97 20.94 15.21
#> 76 194 113 187 6 66.3 164 77 105 117 43.2 175 42
#> 19.22 22.40 22.86 9.92 15.64 22.13 23.60 7.27 19.75 17.46 12.10 21.91 12.43
#> 29 168 159.1 125.1 24.1 57 113.1 52 39 41 168.1 51 43.3
#> 15.45 23.72 10.55 15.65 23.89 14.46 22.86 10.42 15.59 18.02 23.72 18.23 12.10
#> 107 81 24.2 107.1 43.4 92.2 100 136 85 60.1 130 24.3 58
#> 11.18 14.06 23.89 11.18 12.10 22.92 16.07 21.83 16.44 13.15 16.47 23.89 19.34
#> 92.3 15 25 93 52.1 56 108 90.1 128.1 117.1 145 164.1 150
#> 22.92 22.68 6.32 10.33 10.42 12.21 18.29 20.94 20.35 17.46 10.07 23.60 20.33
#> 96 184 16 164.2 56.1 113.2 192 24.4 52.2 180 154 58.1 170
#> 14.54 17.77 8.71 23.60 12.21 22.86 16.44 23.89 10.42 14.82 12.63 19.34 19.54
#> 117.2 23 88 110 170.1 169 139 23.1 82 142 27 67 72
#> 17.46 16.92 18.37 17.56 19.54 22.41 21.49 16.92 24.00 24.00 24.00 24.00 24.00
#> 46 186 74 146 44 146.1 80 54 196 120 104 2 2.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 53 44.1 103 44.2 116 19 165 148 109 141 147 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 191 156 147.1 182 34 126 9.1 1 48.1 17 193 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 34.1 95 119 131.1 173 131.2 196.1 173.1 2.2 34.2 148.1 146.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.2 46.1 151 11 178 17.1 165.1 94 82.1 131.3 191.1 126.1 165.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 54.1 131.4 20 102 142.1 1.1 112 28.1 2.3 27.1 34.3 3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.1 147.2 17.2
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[94]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.002780959 0.587610316 0.534025650
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.97791434 0.01855271 0.29346646
#> grade_iii, Cure model
#> 0.42954342
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 42 12.43 1 49 0 1
#> 158 20.14 1 74 1 0
#> 52 10.42 1 52 0 1
#> 6 15.64 1 39 0 0
#> 56 12.21 1 60 0 0
#> 192 16.44 1 31 1 0
#> 24 23.89 1 38 0 0
#> 149 8.37 1 33 1 0
#> 15 22.68 1 48 0 0
#> 157 15.10 1 47 0 0
#> 167 15.55 1 56 1 0
#> 189 10.51 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 57 14.46 1 45 0 1
#> 100 16.07 1 60 0 0
#> 86 23.81 1 58 0 1
#> 36 21.19 1 48 0 1
#> 164 23.60 1 76 0 1
#> 57.1 14.46 1 45 0 1
#> 52.1 10.42 1 52 0 1
#> 40 18.00 1 28 1 0
#> 194 22.40 1 38 0 1
#> 68 20.62 1 44 0 0
#> 59 10.16 1 NA 1 0
#> 59.1 10.16 1 NA 1 0
#> 127 3.53 1 62 0 1
#> 133 14.65 1 57 0 0
#> 127.1 3.53 1 62 0 1
#> 181 16.46 1 45 0 1
#> 86.1 23.81 1 58 0 1
#> 88 18.37 1 47 0 0
#> 23 16.92 1 61 0 0
#> 96 14.54 1 33 0 1
#> 113 22.86 1 34 0 0
#> 32 20.90 1 37 1 0
#> 45 17.42 1 54 0 1
#> 78 23.88 1 43 0 0
#> 130 16.47 1 53 0 1
#> 194.1 22.40 1 38 0 1
#> 105 19.75 1 60 0 0
#> 190 20.81 1 42 1 0
#> 192.1 16.44 1 31 1 0
#> 128 20.35 1 35 0 1
#> 153 21.33 1 55 1 0
#> 18 15.21 1 49 1 0
#> 88.1 18.37 1 47 0 0
#> 42.1 12.43 1 49 0 1
#> 59.2 10.16 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 133.1 14.65 1 57 0 0
#> 166 19.98 1 48 0 0
#> 68.1 20.62 1 44 0 0
#> 61 10.12 1 36 0 1
#> 130.1 16.47 1 53 0 1
#> 175 21.91 1 43 0 0
#> 150 20.33 1 48 0 0
#> 26 15.77 1 49 0 1
#> 168 23.72 1 70 0 0
#> 111.1 17.45 1 47 0 1
#> 194.2 22.40 1 38 0 1
#> 108 18.29 1 39 0 1
#> 199 19.81 1 NA 0 1
#> 199.1 19.81 1 NA 0 1
#> 78.1 23.88 1 43 0 0
#> 106 16.67 1 49 1 0
#> 145 10.07 1 65 1 0
#> 4 17.64 1 NA 0 1
#> 183 9.24 1 67 1 0
#> 86.2 23.81 1 58 0 1
#> 154 12.63 1 20 1 0
#> 4.1 17.64 1 NA 0 1
#> 113.1 22.86 1 34 0 0
#> 129 23.41 1 53 1 0
#> 139 21.49 1 63 1 0
#> 92 22.92 1 47 0 1
#> 197 21.60 1 69 1 0
#> 23.1 16.92 1 61 0 0
#> 180 14.82 1 37 0 0
#> 36.1 21.19 1 48 0 1
#> 16 8.71 1 71 0 1
#> 77 7.27 1 67 0 1
#> 16.1 8.71 1 71 0 1
#> 29 15.45 1 68 1 0
#> 97 19.14 1 65 0 1
#> 134 17.81 1 47 1 0
#> 136 21.83 1 43 0 1
#> 127.2 3.53 1 62 0 1
#> 41 18.02 1 40 1 0
#> 168.1 23.72 1 70 0 0
#> 4.2 17.64 1 NA 0 1
#> 4.3 17.64 1 NA 0 1
#> 88.2 18.37 1 47 0 0
#> 15.1 22.68 1 48 0 0
#> 169 22.41 1 46 0 0
#> 127.3 3.53 1 62 0 1
#> 10 10.53 1 34 0 0
#> 24.1 23.89 1 38 0 0
#> 133.2 14.65 1 57 0 0
#> 197.1 21.60 1 69 1 0
#> 175.1 21.91 1 43 0 0
#> 49 12.19 1 48 1 0
#> 114 13.68 1 NA 0 0
#> 81 14.06 1 34 0 0
#> 52.2 10.42 1 52 0 1
#> 50 10.02 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 197.2 21.60 1 69 1 0
#> 140 12.68 1 59 1 0
#> 23.2 16.92 1 61 0 0
#> 61.1 10.12 1 36 0 1
#> 110 17.56 1 65 0 1
#> 26.1 15.77 1 49 0 1
#> 94 24.00 0 51 0 1
#> 182 24.00 0 35 0 0
#> 84 24.00 0 39 0 1
#> 112 24.00 0 61 0 0
#> 137 24.00 0 45 1 0
#> 83 24.00 0 6 0 0
#> 119 24.00 0 17 0 0
#> 17 24.00 0 38 0 1
#> 109 24.00 0 48 0 0
#> 109.1 24.00 0 48 0 0
#> 12 24.00 0 63 0 0
#> 160 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 33 24.00 0 53 0 0
#> 67 24.00 0 25 0 0
#> 144 24.00 0 28 0 1
#> 151 24.00 0 42 0 0
#> 191 24.00 0 60 0 1
#> 186 24.00 0 45 1 0
#> 185 24.00 0 44 1 0
#> 196 24.00 0 19 0 0
#> 115 24.00 0 NA 1 0
#> 121 24.00 0 57 1 0
#> 151.1 24.00 0 42 0 0
#> 160.1 24.00 0 31 1 0
#> 84.1 24.00 0 39 0 1
#> 132 24.00 0 55 0 0
#> 196.1 24.00 0 19 0 0
#> 12.1 24.00 0 63 0 0
#> 44 24.00 0 56 0 0
#> 137.1 24.00 0 45 1 0
#> 102 24.00 0 49 0 0
#> 3 24.00 0 31 1 0
#> 112.1 24.00 0 61 0 0
#> 62 24.00 0 71 0 0
#> 95 24.00 0 68 0 1
#> 98 24.00 0 34 1 0
#> 142 24.00 0 53 0 0
#> 122 24.00 0 66 0 0
#> 80 24.00 0 41 0 0
#> 163 24.00 0 66 0 0
#> 120 24.00 0 68 0 1
#> 132.1 24.00 0 55 0 0
#> 83.1 24.00 0 6 0 0
#> 83.2 24.00 0 6 0 0
#> 17.1 24.00 0 38 0 1
#> 142.1 24.00 0 53 0 0
#> 118 24.00 0 44 1 0
#> 176 24.00 0 43 0 1
#> 12.2 24.00 0 63 0 0
#> 115.1 24.00 0 NA 1 0
#> 151.2 24.00 0 42 0 0
#> 84.2 24.00 0 39 0 1
#> 146 24.00 0 63 1 0
#> 104 24.00 0 50 1 0
#> 141 24.00 0 44 1 0
#> 80.1 24.00 0 41 0 0
#> 191.1 24.00 0 60 0 1
#> 94.1 24.00 0 51 0 1
#> 191.2 24.00 0 60 0 1
#> 126 24.00 0 48 0 0
#> 87 24.00 0 27 0 0
#> 95.1 24.00 0 68 0 1
#> 147 24.00 0 76 1 0
#> 147.1 24.00 0 76 1 0
#> 7 24.00 0 37 1 0
#> 95.2 24.00 0 68 0 1
#> 173 24.00 0 19 0 1
#> 19 24.00 0 57 0 1
#> 80.2 24.00 0 41 0 0
#> 152 24.00 0 36 0 1
#> 173.1 24.00 0 19 0 1
#> 191.3 24.00 0 60 0 1
#> 152.1 24.00 0 36 0 1
#> 151.3 24.00 0 42 0 0
#> 178 24.00 0 52 1 0
#> 120.1 24.00 0 68 0 1
#> 200 24.00 0 64 0 0
#> 163.1 24.00 0 66 0 0
#> 185.1 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 95.3 24.00 0 68 0 1
#> 193 24.00 0 45 0 1
#> 19.1 24.00 0 57 0 1
#> 19.2 24.00 0 57 0 1
#> 173.2 24.00 0 19 0 1
#> 161 24.00 0 45 0 0
#> 80.3 24.00 0 41 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.978 NA NA NA
#> 2 age, Cure model 0.0186 NA NA NA
#> 3 grade_ii, Cure model 0.293 NA NA NA
#> 4 grade_iii, Cure model 0.430 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00278 NA NA NA
#> 2 grade_ii, Survival model 0.588 NA NA NA
#> 3 grade_iii, Survival model 0.534 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.97791 0.01855 0.29347 0.42954
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.8
#> Residual Deviance: 251.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.97791434 0.01855271 0.29346646 0.42954342
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.002780959 0.587610316 0.534025650
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.87004995 0.54244742 0.90267909 0.75986026 0.88312532 0.72350711
#> [7] 0.03866924 0.95876457 0.30302992 0.78823509 0.76706426 0.97085658
#> [13] 0.82971516 0.73815680 0.14863454 0.46712693 0.23096748 0.82971516
#> [19] 0.90267909 0.62124414 0.34354401 0.50549616 0.97684465 0.80218485
#> [25] 0.97684465 0.71599783 0.14863454 0.57820950 0.66990439 0.82282671
#> [31] 0.27581641 0.48649803 0.66200877 0.09508395 0.70091116 0.34354401
#> [37] 0.56043737 0.49609009 0.72350711 0.52404437 0.45693335 0.78124825
#> [43] 0.57820950 0.87004995 0.64612676 0.80218485 0.55145287 0.50549616
#> [49] 0.92163816 0.70091116 0.37921912 0.53325723 0.74550505 0.19784350
#> [55] 0.64612676 0.34354401 0.60408709 0.09508395 0.69316303 0.93416860
#> [61] 0.94040644 0.14863454 0.85672135 0.27581641 0.24686051 0.44648404
#> [67] 0.26171602 0.41504193 0.66990439 0.79521328 0.46712693 0.94659631
#> [73] 0.96483056 0.94659631 0.77419440 0.56939580 0.62965294 0.40319835
#> [79] 0.97684465 0.61272635 0.19784350 0.57820950 0.30302992 0.32990066
#> [85] 0.97684465 0.89618115 0.03866924 0.80218485 0.41504193 0.37921912
#> [91] 0.88967854 0.84322639 0.90267909 0.86339162 0.41504193 0.85000388
#> [97] 0.66990439 0.92163816 0.63794535 0.74550505 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 42 158 52 6 56 192 24 149 15 157 167 91 57
#> 12.43 20.14 10.42 15.64 12.21 16.44 23.89 8.37 22.68 15.10 15.55 5.33 14.46
#> 100 86 36 164 57.1 52.1 40 194 68 127 133 127.1 181
#> 16.07 23.81 21.19 23.60 14.46 10.42 18.00 22.40 20.62 3.53 14.65 3.53 16.46
#> 86.1 88 23 96 113 32 45 78 130 194.1 105 190 192.1
#> 23.81 18.37 16.92 14.54 22.86 20.90 17.42 23.88 16.47 22.40 19.75 20.81 16.44
#> 128 153 18 88.1 42.1 111 133.1 166 68.1 61 130.1 175 150
#> 20.35 21.33 15.21 18.37 12.43 17.45 14.65 19.98 20.62 10.12 16.47 21.91 20.33
#> 26 168 111.1 194.2 108 78.1 106 145 183 86.2 154 113.1 129
#> 15.77 23.72 17.45 22.40 18.29 23.88 16.67 10.07 9.24 23.81 12.63 22.86 23.41
#> 139 92 197 23.1 180 36.1 16 77 16.1 29 97 134 136
#> 21.49 22.92 21.60 16.92 14.82 21.19 8.71 7.27 8.71 15.45 19.14 17.81 21.83
#> 127.2 41 168.1 88.2 15.1 169 127.3 10 24.1 133.2 197.1 175.1 49
#> 3.53 18.02 23.72 18.37 22.68 22.41 3.53 10.53 23.89 14.65 21.60 21.91 12.19
#> 81 52.2 177 197.2 140 23.2 61.1 110 26.1 94 182 84 112
#> 14.06 10.42 12.53 21.60 12.68 16.92 10.12 17.56 15.77 24.00 24.00 24.00 24.00
#> 137 83 119 17 109 109.1 12 160 28 33 67 144 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191 186 185 196 121 151.1 160.1 84.1 132 196.1 12.1 44 137.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 3 112.1 62 95 98 142 122 80 163 120 132.1 83.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83.2 17.1 142.1 118 176 12.2 151.2 84.2 146 104 141 80.1 191.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.1 191.2 126 87 95.1 147 147.1 7 95.2 173 19 80.2 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173.1 191.3 152.1 151.3 178 120.1 200 163.1 185.1 82 95.3 193 19.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19.2 173.2 161 80.3
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[95]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01884671 0.39630381 -0.12216701
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.683585305 0.009658887 0.251282160
#> grade_iii, Cure model
#> 0.859606385
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 32 20.90 1 37 1 0
#> 117 17.46 1 26 0 1
#> 187 9.92 1 39 1 0
#> 149 8.37 1 33 1 0
#> 107 11.18 1 54 1 0
#> 23 16.92 1 61 0 0
#> 101 9.97 1 10 0 1
#> 136 21.83 1 43 0 1
#> 107.1 11.18 1 54 1 0
#> 192 16.44 1 31 1 0
#> 51 18.23 1 83 0 1
#> 190 20.81 1 42 1 0
#> 41 18.02 1 40 1 0
#> 158 20.14 1 74 1 0
#> 4 17.64 1 NA 0 1
#> 29 15.45 1 68 1 0
#> 111 17.45 1 47 0 1
#> 140 12.68 1 59 1 0
#> 107.2 11.18 1 54 1 0
#> 57 14.46 1 45 0 1
#> 8 18.43 1 32 0 0
#> 184 17.77 1 38 0 0
#> 92 22.92 1 47 0 1
#> 43 12.10 1 61 0 1
#> 79 16.23 1 54 1 0
#> 40 18.00 1 28 1 0
#> 51.1 18.23 1 83 0 1
#> 30 17.43 1 78 0 0
#> 170 19.54 1 43 0 1
#> 23.1 16.92 1 61 0 0
#> 55 19.34 1 69 0 1
#> 124 9.73 1 NA 1 0
#> 8.1 18.43 1 32 0 0
#> 16 8.71 1 71 0 1
#> 154 12.63 1 20 1 0
#> 32.1 20.90 1 37 1 0
#> 199 19.81 1 NA 0 1
#> 99 21.19 1 38 0 1
#> 88 18.37 1 47 0 0
#> 190.1 20.81 1 42 1 0
#> 164 23.60 1 76 0 1
#> 101.1 9.97 1 10 0 1
#> 170.1 19.54 1 43 0 1
#> 90 20.94 1 50 0 1
#> 79.1 16.23 1 54 1 0
#> 92.1 22.92 1 47 0 1
#> 30.1 17.43 1 78 0 0
#> 111.1 17.45 1 47 0 1
#> 39 15.59 1 37 0 1
#> 60 13.15 1 38 1 0
#> 50 10.02 1 NA 1 0
#> 45 17.42 1 54 0 1
#> 129 23.41 1 53 1 0
#> 111.2 17.45 1 47 0 1
#> 108 18.29 1 39 0 1
#> 105 19.75 1 60 0 0
#> 140.1 12.68 1 59 1 0
#> 4.1 17.64 1 NA 0 1
#> 140.2 12.68 1 59 1 0
#> 114 13.68 1 NA 0 0
#> 149.1 8.37 1 33 1 0
#> 86 23.81 1 58 0 1
#> 125 15.65 1 67 1 0
#> 154.1 12.63 1 20 1 0
#> 134 17.81 1 47 1 0
#> 57.1 14.46 1 45 0 1
#> 42 12.43 1 49 0 1
#> 133 14.65 1 57 0 0
#> 89 11.44 1 NA 0 0
#> 45.1 17.42 1 54 0 1
#> 81 14.06 1 34 0 0
#> 30.2 17.43 1 78 0 0
#> 89.1 11.44 1 NA 0 0
#> 36 21.19 1 48 0 1
#> 154.2 12.63 1 20 1 0
#> 124.1 9.73 1 NA 1 0
#> 187.1 9.92 1 39 1 0
#> 49 12.19 1 48 1 0
#> 5 16.43 1 51 0 1
#> 50.1 10.02 1 NA 1 0
#> 123 13.00 1 44 1 0
#> 139 21.49 1 63 1 0
#> 171 16.57 1 41 0 1
#> 168 23.72 1 70 0 0
#> 92.2 22.92 1 47 0 1
#> 40.1 18.00 1 28 1 0
#> 111.3 17.45 1 47 0 1
#> 107.3 11.18 1 54 1 0
#> 39.1 15.59 1 37 0 1
#> 36.1 21.19 1 48 0 1
#> 169 22.41 1 46 0 0
#> 45.2 17.42 1 54 0 1
#> 66 22.13 1 53 0 0
#> 14 12.89 1 21 0 0
#> 106 16.67 1 49 1 0
#> 149.2 8.37 1 33 1 0
#> 101.2 9.97 1 10 0 1
#> 130 16.47 1 53 0 1
#> 123.1 13.00 1 44 1 0
#> 29.1 15.45 1 68 1 0
#> 170.2 19.54 1 43 0 1
#> 97 19.14 1 65 0 1
#> 42.1 12.43 1 49 0 1
#> 139.1 21.49 1 63 1 0
#> 6 15.64 1 39 0 0
#> 41.1 18.02 1 40 1 0
#> 100 16.07 1 60 0 0
#> 88.1 18.37 1 47 0 0
#> 105.1 19.75 1 60 0 0
#> 107.4 11.18 1 54 1 0
#> 100.1 16.07 1 60 0 0
#> 130.1 16.47 1 53 0 1
#> 186 24.00 0 45 1 0
#> 196 24.00 0 19 0 0
#> 176 24.00 0 43 0 1
#> 147 24.00 0 76 1 0
#> 38 24.00 0 31 1 0
#> 147.1 24.00 0 76 1 0
#> 44 24.00 0 56 0 0
#> 141 24.00 0 44 1 0
#> 120 24.00 0 68 0 1
#> 83 24.00 0 6 0 0
#> 67 24.00 0 25 0 0
#> 193 24.00 0 45 0 1
#> 21 24.00 0 47 0 0
#> 178 24.00 0 52 1 0
#> 48 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 17 24.00 0 38 0 1
#> 62 24.00 0 71 0 0
#> 147.2 24.00 0 76 1 0
#> 165 24.00 0 47 0 0
#> 83.1 24.00 0 6 0 0
#> 62.1 24.00 0 71 0 0
#> 11 24.00 0 42 0 1
#> 47 24.00 0 38 0 1
#> 28 24.00 0 67 1 0
#> 12 24.00 0 63 0 0
#> 62.2 24.00 0 71 0 0
#> 109 24.00 0 48 0 0
#> 38.1 24.00 0 31 1 0
#> 176.1 24.00 0 43 0 1
#> 118 24.00 0 44 1 0
#> 11.1 24.00 0 42 0 1
#> 141.1 24.00 0 44 1 0
#> 102 24.00 0 49 0 0
#> 176.2 24.00 0 43 0 1
#> 144 24.00 0 28 0 1
#> 72 24.00 0 40 0 1
#> 116 24.00 0 58 0 1
#> 156 24.00 0 50 1 0
#> 178.1 24.00 0 52 1 0
#> 147.3 24.00 0 76 1 0
#> 74 24.00 0 43 0 1
#> 148 24.00 0 61 1 0
#> 65 24.00 0 57 1 0
#> 141.2 24.00 0 44 1 0
#> 20 24.00 0 46 1 0
#> 182 24.00 0 35 0 0
#> 144.1 24.00 0 28 0 1
#> 65.1 24.00 0 57 1 0
#> 137 24.00 0 45 1 0
#> 17.1 24.00 0 38 0 1
#> 141.3 24.00 0 44 1 0
#> 137.1 24.00 0 45 1 0
#> 186.1 24.00 0 45 1 0
#> 84 24.00 0 39 0 1
#> 98 24.00 0 34 1 0
#> 120.1 24.00 0 68 0 1
#> 62.3 24.00 0 71 0 0
#> 163 24.00 0 66 0 0
#> 94 24.00 0 51 0 1
#> 3 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 142 24.00 0 53 0 0
#> 193.1 24.00 0 45 0 1
#> 71 24.00 0 51 0 0
#> 94.1 24.00 0 51 0 1
#> 196.1 24.00 0 19 0 0
#> 185 24.00 0 44 1 0
#> 200 24.00 0 64 0 0
#> 118.1 24.00 0 44 1 0
#> 182.1 24.00 0 35 0 0
#> 104 24.00 0 50 1 0
#> 80 24.00 0 41 0 0
#> 138 24.00 0 44 1 0
#> 67.1 24.00 0 25 0 0
#> 115 24.00 0 NA 1 0
#> 178.2 24.00 0 52 1 0
#> 72.1 24.00 0 40 0 1
#> 103 24.00 0 56 1 0
#> 1.1 24.00 0 23 1 0
#> 102.1 24.00 0 49 0 0
#> 103.1 24.00 0 56 1 0
#> 143 24.00 0 51 0 0
#> 146 24.00 0 63 1 0
#> 87 24.00 0 27 0 0
#> 7 24.00 0 37 1 0
#> 141.4 24.00 0 44 1 0
#> 148.1 24.00 0 61 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.684 NA NA NA
#> 2 age, Cure model 0.00966 NA NA NA
#> 3 grade_ii, Cure model 0.251 NA NA NA
#> 4 grade_iii, Cure model 0.860 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0188 NA NA NA
#> 2 grade_ii, Survival model 0.396 NA NA NA
#> 3 grade_iii, Survival model -0.122 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.683585 0.009659 0.251282 0.859606
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 254.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.683585305 0.009658887 0.251282160 0.859606385
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01884671 0.39630381 -0.12216701
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 1.564075e-02 1.311101e-01 8.824526e-01 9.409499e-01 7.352522e-01
#> [6] 2.216033e-01 8.258296e-01 3.785160e-03 7.352522e-01 2.858429e-01
#> [11] 8.007723e-02 2.043514e-02 9.215532e-02 2.563173e-02 4.126405e-01
#> [16] 1.381830e-01 5.658967e-01 7.352522e-01 4.559887e-01 5.479332e-02
#> [21] 1.242078e-01 5.631877e-04 7.172555e-01 3.092381e-01 1.047306e-01
#> [26] 8.007723e-02 1.679677e-01 3.501608e-02 2.216033e-01 4.597034e-02
#> [31] 5.479332e-02 9.210973e-01 6.154929e-01 1.564075e-02 7.789020e-03
#> [36] 6.420520e-02 2.043514e-02 7.279517e-05 8.258296e-01 3.501608e-02
#> [41] 1.323960e-02 3.092381e-01 5.631877e-04 1.679677e-01 1.381830e-01
#> [46] 3.852279e-01 5.020220e-01 1.935235e-01 2.644246e-04 1.381830e-01
#> [51] 7.450555e-02 2.857633e-02 5.658967e-01 5.658967e-01 9.409499e-01
#> [56] 4.245374e-07 3.586452e-01 6.154929e-01 1.174963e-01 4.559887e-01
#> [61] 6.650132e-01 4.411665e-01 1.935235e-01 4.863577e-01 1.679677e-01
#> [66] 7.789020e-03 6.154929e-01 8.824526e-01 6.995780e-01 2.973884e-01
#> [71] 5.178213e-01 4.997295e-03 2.525226e-01 1.236005e-05 5.631877e-04
#> [76] 1.047306e-01 1.381830e-01 7.352522e-01 3.852279e-01 7.789020e-03
#> [81] 1.947974e-03 1.935235e-01 2.770919e-03 5.496096e-01 2.419432e-01
#> [86] 9.409499e-01 8.258296e-01 2.633709e-01 5.178213e-01 4.126405e-01
#> [91] 3.501608e-02 5.023862e-02 6.650132e-01 4.997295e-03 3.718129e-01
#> [96] 9.215532e-02 3.333219e-01 6.420520e-02 2.857633e-02 7.352522e-01
#> [101] 3.333219e-01 2.633709e-01 0.000000e+00 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 32 117 187 149 107 23 101 136 107.1 192 51 190 41
#> 20.90 17.46 9.92 8.37 11.18 16.92 9.97 21.83 11.18 16.44 18.23 20.81 18.02
#> 158 29 111 140 107.2 57 8 184 92 43 79 40 51.1
#> 20.14 15.45 17.45 12.68 11.18 14.46 18.43 17.77 22.92 12.10 16.23 18.00 18.23
#> 30 170 23.1 55 8.1 16 154 32.1 99 88 190.1 164 101.1
#> 17.43 19.54 16.92 19.34 18.43 8.71 12.63 20.90 21.19 18.37 20.81 23.60 9.97
#> 170.1 90 79.1 92.1 30.1 111.1 39 60 45 129 111.2 108 105
#> 19.54 20.94 16.23 22.92 17.43 17.45 15.59 13.15 17.42 23.41 17.45 18.29 19.75
#> 140.1 140.2 149.1 86 125 154.1 134 57.1 42 133 45.1 81 30.2
#> 12.68 12.68 8.37 23.81 15.65 12.63 17.81 14.46 12.43 14.65 17.42 14.06 17.43
#> 36 154.2 187.1 49 5 123 139 171 168 92.2 40.1 111.3 107.3
#> 21.19 12.63 9.92 12.19 16.43 13.00 21.49 16.57 23.72 22.92 18.00 17.45 11.18
#> 39.1 36.1 169 45.2 66 14 106 149.2 101.2 130 123.1 29.1 170.2
#> 15.59 21.19 22.41 17.42 22.13 12.89 16.67 8.37 9.97 16.47 13.00 15.45 19.54
#> 97 42.1 139.1 6 41.1 100 88.1 105.1 107.4 100.1 130.1 186 196
#> 19.14 12.43 21.49 15.64 18.02 16.07 18.37 19.75 11.18 16.07 16.47 24.00 24.00
#> 176 147 38 147.1 44 141 120 83 67 193 21 178 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 17 62 147.2 165 83.1 62.1 11 47 28 12 62.2 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38.1 176.1 118 11.1 141.1 102 176.2 144 72 116 156 178.1 147.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74 148 65 141.2 20 182 144.1 65.1 137 17.1 141.3 137.1 186.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 98 120.1 62.3 163 94 3 53 142 193.1 71 94.1 196.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 200 118.1 182.1 104 80 138 67.1 178.2 72.1 103 1.1 102.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103.1 143 146 87 7 141.4 148.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[96]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004032065 0.476665951 0.506661626
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.320685756 0.007772613 0.108806310
#> grade_iii, Cure model
#> 0.404973844
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 58 19.34 1 39 0 0
#> 167 15.55 1 56 1 0
#> 32 20.90 1 37 1 0
#> 197 21.60 1 69 1 0
#> 97 19.14 1 65 0 1
#> 8 18.43 1 32 0 0
#> 30 17.43 1 78 0 0
#> 167.1 15.55 1 56 1 0
#> 5 16.43 1 51 0 1
#> 55 19.34 1 69 0 1
#> 105 19.75 1 60 0 0
#> 100 16.07 1 60 0 0
#> 114 13.68 1 NA 0 0
#> 129 23.41 1 53 1 0
#> 61 10.12 1 36 0 1
#> 107 11.18 1 54 1 0
#> 105.1 19.75 1 60 0 0
#> 40 18.00 1 28 1 0
#> 188 16.16 1 46 0 1
#> 25 6.32 1 34 1 0
#> 124 9.73 1 NA 1 0
#> 194 22.40 1 38 0 1
#> 13 14.34 1 54 0 1
#> 79 16.23 1 54 1 0
#> 43 12.10 1 61 0 1
#> 123 13.00 1 44 1 0
#> 194.1 22.40 1 38 0 1
#> 49 12.19 1 48 1 0
#> 179 18.63 1 42 0 0
#> 150 20.33 1 48 0 0
#> 187 9.92 1 39 1 0
#> 171 16.57 1 41 0 1
#> 18 15.21 1 49 1 0
#> 128 20.35 1 35 0 1
#> 25.1 6.32 1 34 1 0
#> 55.1 19.34 1 69 0 1
#> 133 14.65 1 57 0 0
#> 114.1 13.68 1 NA 0 0
#> 123.1 13.00 1 44 1 0
#> 58.1 19.34 1 39 0 0
#> 40.1 18.00 1 28 1 0
#> 49.1 12.19 1 48 1 0
#> 189 10.51 1 NA 1 0
#> 60 13.15 1 38 1 0
#> 149 8.37 1 33 1 0
#> 100.1 16.07 1 60 0 0
#> 114.2 13.68 1 NA 0 0
#> 25.2 6.32 1 34 1 0
#> 149.1 8.37 1 33 1 0
#> 66 22.13 1 53 0 0
#> 124.1 9.73 1 NA 1 0
#> 24 23.89 1 38 0 0
#> 111 17.45 1 47 0 1
#> 139 21.49 1 63 1 0
#> 166 19.98 1 48 0 0
#> 52 10.42 1 52 0 1
#> 129.1 23.41 1 53 1 0
#> 5.1 16.43 1 51 0 1
#> 6 15.64 1 39 0 0
#> 45 17.42 1 54 0 1
#> 88 18.37 1 47 0 0
#> 32.1 20.90 1 37 1 0
#> 42 12.43 1 49 0 1
#> 39 15.59 1 37 0 1
#> 123.2 13.00 1 44 1 0
#> 153 21.33 1 55 1 0
#> 157 15.10 1 47 0 0
#> 86 23.81 1 58 0 1
#> 90 20.94 1 50 0 1
#> 90.1 20.94 1 50 0 1
#> 169 22.41 1 46 0 0
#> 15 22.68 1 48 0 0
#> 149.2 8.37 1 33 1 0
#> 89 11.44 1 NA 0 0
#> 170 19.54 1 43 0 1
#> 189.1 10.51 1 NA 1 0
#> 57 14.46 1 45 0 1
#> 58.2 19.34 1 39 0 0
#> 77 7.27 1 67 0 1
#> 155 13.08 1 26 0 0
#> 41 18.02 1 40 1 0
#> 51 18.23 1 83 0 1
#> 63 22.77 1 31 1 0
#> 167.2 15.55 1 56 1 0
#> 130 16.47 1 53 0 1
#> 78 23.88 1 43 0 0
#> 66.1 22.13 1 53 0 0
#> 167.3 15.55 1 56 1 0
#> 106 16.67 1 49 1 0
#> 76 19.22 1 54 0 1
#> 85 16.44 1 36 0 0
#> 154 12.63 1 20 1 0
#> 8.1 18.43 1 32 0 0
#> 14 12.89 1 21 0 0
#> 40.2 18.00 1 28 1 0
#> 39.1 15.59 1 37 0 1
#> 159 10.55 1 50 0 1
#> 76.1 19.22 1 54 0 1
#> 15.1 22.68 1 48 0 0
#> 51.1 18.23 1 83 0 1
#> 43.1 12.10 1 61 0 1
#> 32.2 20.90 1 37 1 0
#> 88.1 18.37 1 47 0 0
#> 63.1 22.77 1 31 1 0
#> 157.1 15.10 1 47 0 0
#> 97.1 19.14 1 65 0 1
#> 150.1 20.33 1 48 0 0
#> 89.1 11.44 1 NA 0 0
#> 18.1 15.21 1 49 1 0
#> 57.1 14.46 1 45 0 1
#> 134 17.81 1 47 1 0
#> 91 5.33 1 61 0 1
#> 173 24.00 0 19 0 1
#> 162 24.00 0 51 0 0
#> 9 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 141 24.00 0 44 1 0
#> 193 24.00 0 45 0 1
#> 12 24.00 0 63 0 0
#> 53 24.00 0 32 0 1
#> 35 24.00 0 51 0 0
#> 11 24.00 0 42 0 1
#> 95 24.00 0 68 0 1
#> 109 24.00 0 48 0 0
#> 98 24.00 0 34 1 0
#> 65 24.00 0 57 1 0
#> 151 24.00 0 42 0 0
#> 47 24.00 0 38 0 1
#> 73 24.00 0 NA 0 1
#> 20 24.00 0 46 1 0
#> 182 24.00 0 35 0 0
#> 102 24.00 0 49 0 0
#> 65.1 24.00 0 57 1 0
#> 137 24.00 0 45 1 0
#> 163 24.00 0 66 0 0
#> 115 24.00 0 NA 1 0
#> 9.1 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 200 24.00 0 64 0 0
#> 47.1 24.00 0 38 0 1
#> 172 24.00 0 41 0 0
#> 104 24.00 0 50 1 0
#> 156 24.00 0 50 1 0
#> 186 24.00 0 45 1 0
#> 84 24.00 0 39 0 1
#> 116 24.00 0 58 0 1
#> 11.1 24.00 0 42 0 1
#> 98.1 24.00 0 34 1 0
#> 67 24.00 0 25 0 0
#> 102.1 24.00 0 49 0 0
#> 22 24.00 0 52 1 0
#> 75 24.00 0 21 1 0
#> 137.1 24.00 0 45 1 0
#> 147 24.00 0 76 1 0
#> 65.2 24.00 0 57 1 0
#> 2 24.00 0 9 0 0
#> 135 24.00 0 58 1 0
#> 31 24.00 0 36 0 1
#> 82 24.00 0 34 0 0
#> 163.1 24.00 0 66 0 0
#> 172.1 24.00 0 41 0 0
#> 120.1 24.00 0 68 0 1
#> 152 24.00 0 36 0 1
#> 146 24.00 0 63 1 0
#> 82.1 24.00 0 34 0 0
#> 53.1 24.00 0 32 0 1
#> 65.3 24.00 0 57 1 0
#> 95.1 24.00 0 68 0 1
#> 151.1 24.00 0 42 0 0
#> 53.2 24.00 0 32 0 1
#> 141.1 24.00 0 44 1 0
#> 73.1 24.00 0 NA 0 1
#> 103 24.00 0 56 1 0
#> 178 24.00 0 52 1 0
#> 12.1 24.00 0 63 0 0
#> 11.2 24.00 0 42 0 1
#> 185 24.00 0 44 1 0
#> 161 24.00 0 45 0 0
#> 102.2 24.00 0 49 0 0
#> 156.1 24.00 0 50 1 0
#> 73.2 24.00 0 NA 0 1
#> 83 24.00 0 6 0 0
#> 144 24.00 0 28 0 1
#> 7 24.00 0 37 1 0
#> 82.2 24.00 0 34 0 0
#> 165 24.00 0 47 0 0
#> 174 24.00 0 49 1 0
#> 82.3 24.00 0 34 0 0
#> 122 24.00 0 66 0 0
#> 7.1 24.00 0 37 1 0
#> 28 24.00 0 67 1 0
#> 146.1 24.00 0 63 1 0
#> 75.1 24.00 0 21 1 0
#> 28.1 24.00 0 67 1 0
#> 17 24.00 0 38 0 1
#> 131 24.00 0 66 0 0
#> 137.2 24.00 0 45 1 0
#> 34 24.00 0 36 0 0
#> 132 24.00 0 55 0 0
#> 173.1 24.00 0 19 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.321 NA NA NA
#> 2 age, Cure model 0.00777 NA NA NA
#> 3 grade_ii, Cure model 0.109 NA NA NA
#> 4 grade_iii, Cure model 0.405 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00403 NA NA NA
#> 2 grade_ii, Survival model 0.477 NA NA NA
#> 3 grade_iii, Survival model 0.507 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.320686 0.007773 0.108806 0.404974
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.3
#> Residual Deviance: 255.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.320685756 0.007772613 0.108806310 0.404973844
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004032065 0.476665951 0.506661626
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.33886663 0.68669101 0.23938399 0.18461743 0.40602302 0.43501851
#> [7] 0.54982428 0.68669101 0.60552381 0.33886663 0.30851377 0.64170966
#> [13] 0.05804324 0.91870995 0.89359188 0.30851377 0.50311611 0.63268625
#> [19] 0.96785478 0.14023290 0.78264984 0.62361384 0.87682433 0.80875076
#> [25] 0.14023290 0.85996074 0.42525597 0.27857865 0.92702279 0.57788003
#> [31] 0.72143549 0.26862163 0.96785478 0.33886663 0.75640629 0.80875076
#> [37] 0.33886663 0.50311611 0.85996074 0.79137138 0.93530767 0.64170966
#> [43] 0.96785478 0.93530767 0.16213106 0.00720650 0.54046404 0.19606780
#> [49] 0.29838194 0.91036423 0.05804324 0.60552381 0.65973779 0.55922772
#> [55] 0.45442889 0.23938399 0.85143220 0.66883250 0.80875076 0.20735403
#> [61] 0.73888517 0.04164691 0.21846487 0.21846487 0.12797827 0.10499757
#> [67] 0.93530767 0.32872563 0.76523932 0.33886663 0.95967965 0.80005637
#> [73] 0.49338814 0.47398357 0.08288405 0.68669101 0.58712106 0.02311688
#> [79] 0.16213106 0.68669101 0.56857850 0.38653450 0.59631284 0.84287261
#> [85] 0.43501851 0.83427057 0.50311611 0.66883250 0.90199196 0.38653450
#> [91] 0.10499757 0.47398357 0.87682433 0.23938399 0.45442889 0.08288405
#> [97] 0.73888517 0.40602302 0.27857865 0.72143549 0.76523932 0.53104290
#> [103] 0.99192904 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 58 167 32 197 97 8 30 167.1 5 55 105 100 129
#> 19.34 15.55 20.90 21.60 19.14 18.43 17.43 15.55 16.43 19.34 19.75 16.07 23.41
#> 61 107 105.1 40 188 25 194 13 79 43 123 194.1 49
#> 10.12 11.18 19.75 18.00 16.16 6.32 22.40 14.34 16.23 12.10 13.00 22.40 12.19
#> 179 150 187 171 18 128 25.1 55.1 133 123.1 58.1 40.1 49.1
#> 18.63 20.33 9.92 16.57 15.21 20.35 6.32 19.34 14.65 13.00 19.34 18.00 12.19
#> 60 149 100.1 25.2 149.1 66 24 111 139 166 52 129.1 5.1
#> 13.15 8.37 16.07 6.32 8.37 22.13 23.89 17.45 21.49 19.98 10.42 23.41 16.43
#> 6 45 88 32.1 42 39 123.2 153 157 86 90 90.1 169
#> 15.64 17.42 18.37 20.90 12.43 15.59 13.00 21.33 15.10 23.81 20.94 20.94 22.41
#> 15 149.2 170 57 58.2 77 155 41 51 63 167.2 130 78
#> 22.68 8.37 19.54 14.46 19.34 7.27 13.08 18.02 18.23 22.77 15.55 16.47 23.88
#> 66.1 167.3 106 76 85 154 8.1 14 40.2 39.1 159 76.1 15.1
#> 22.13 15.55 16.67 19.22 16.44 12.63 18.43 12.89 18.00 15.59 10.55 19.22 22.68
#> 51.1 43.1 32.2 88.1 63.1 157.1 97.1 150.1 18.1 57.1 134 91 173
#> 18.23 12.10 20.90 18.37 22.77 15.10 19.14 20.33 15.21 14.46 17.81 5.33 24.00
#> 162 9 120 141 193 12 53 35 11 95 109 98 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151 47 20 182 102 65.1 137 163 9.1 19 200 47.1 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 156 186 84 116 11.1 98.1 67 102.1 22 75 137.1 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.2 2 135 31 82 163.1 172.1 120.1 152 146 82.1 53.1 65.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95.1 151.1 53.2 141.1 103 178 12.1 11.2 185 161 102.2 156.1 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 7 82.2 165 174 82.3 122 7.1 28 146.1 75.1 28.1 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 137.2 34 132 173.1
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[97]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002149028 0.601443083 0.481754732
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.57611028 0.01435053 -0.18181852
#> grade_iii, Cure model
#> 0.82957276
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 153 21.33 1 55 1 0
#> 190 20.81 1 42 1 0
#> 29 15.45 1 68 1 0
#> 8 18.43 1 32 0 0
#> 130 16.47 1 53 0 1
#> 57 14.46 1 45 0 1
#> 145 10.07 1 65 1 0
#> 187 9.92 1 39 1 0
#> 24 23.89 1 38 0 0
#> 81 14.06 1 34 0 0
#> 24.1 23.89 1 38 0 0
#> 158 20.14 1 74 1 0
#> 50 10.02 1 NA 1 0
#> 88 18.37 1 47 0 0
#> 180 14.82 1 37 0 0
#> 184 17.77 1 38 0 0
#> 168 23.72 1 70 0 0
#> 108 18.29 1 39 0 1
#> 155 13.08 1 26 0 0
#> 59 10.16 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 4 17.64 1 NA 0 1
#> 155.1 13.08 1 26 0 0
#> 8.1 18.43 1 32 0 0
#> 168.1 23.72 1 70 0 0
#> 60 13.15 1 38 1 0
#> 169 22.41 1 46 0 0
#> 8.2 18.43 1 32 0 0
#> 96 14.54 1 33 0 1
#> 197 21.60 1 69 1 0
#> 154 12.63 1 20 1 0
#> 155.2 13.08 1 26 0 0
#> 52 10.42 1 52 0 1
#> 190.1 20.81 1 42 1 0
#> 117 17.46 1 26 0 1
#> 179 18.63 1 42 0 0
#> 164 23.60 1 76 0 1
#> 184.1 17.77 1 38 0 0
#> 154.1 12.63 1 20 1 0
#> 59.1 10.16 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 39 15.59 1 37 0 1
#> 78 23.88 1 43 0 0
#> 43 12.10 1 61 0 1
#> 49 12.19 1 48 1 0
#> 15 22.68 1 48 0 0
#> 39.1 15.59 1 37 0 1
#> 32 20.90 1 37 1 0
#> 97 19.14 1 65 0 1
#> 180.1 14.82 1 37 0 0
#> 26 15.77 1 49 0 1
#> 127 3.53 1 62 0 1
#> 140 12.68 1 59 1 0
#> 154.2 12.63 1 20 1 0
#> 157 15.10 1 47 0 0
#> 37 12.52 1 57 1 0
#> 68 20.62 1 44 0 0
#> 159 10.55 1 50 0 1
#> 63 22.77 1 31 1 0
#> 14 12.89 1 21 0 0
#> 110 17.56 1 65 0 1
#> 45 17.42 1 54 0 1
#> 129 23.41 1 53 1 0
#> 139 21.49 1 63 1 0
#> 106 16.67 1 49 1 0
#> 70 7.38 1 30 1 0
#> 154.3 12.63 1 20 1 0
#> 180.2 14.82 1 37 0 0
#> 166 19.98 1 48 0 0
#> 6 15.64 1 39 0 0
#> 55 19.34 1 69 0 1
#> 32.1 20.90 1 37 1 0
#> 15.1 22.68 1 48 0 0
#> 157.1 15.10 1 47 0 0
#> 93 10.33 1 52 0 1
#> 25 6.32 1 34 1 0
#> 190.2 20.81 1 42 1 0
#> 26.1 15.77 1 49 0 1
#> 61 10.12 1 36 0 1
#> 15.2 22.68 1 48 0 0
#> 177 12.53 1 75 0 0
#> 77 7.27 1 67 0 1
#> 130.1 16.47 1 53 0 1
#> 88.1 18.37 1 47 0 0
#> 68.1 20.62 1 44 0 0
#> 57.1 14.46 1 45 0 1
#> 127.1 3.53 1 62 0 1
#> 51 18.23 1 83 0 1
#> 183 9.24 1 67 1 0
#> 69.1 23.23 1 25 0 1
#> 110.1 17.56 1 65 0 1
#> 51.1 18.23 1 83 0 1
#> 76 19.22 1 54 0 1
#> 42 12.43 1 49 0 1
#> 199 19.81 1 NA 0 1
#> 105 19.75 1 60 0 0
#> 66 22.13 1 53 0 0
#> 41 18.02 1 40 1 0
#> 154.4 12.63 1 20 1 0
#> 59.2 10.16 1 NA 1 0
#> 49.1 12.19 1 48 1 0
#> 29.1 15.45 1 68 1 0
#> 171 16.57 1 41 0 1
#> 110.2 17.56 1 65 0 1
#> 92 22.92 1 47 0 1
#> 145.1 10.07 1 65 1 0
#> 127.2 3.53 1 62 0 1
#> 63.1 22.77 1 31 1 0
#> 69.2 23.23 1 25 0 1
#> 37.1 12.52 1 57 1 0
#> 86 23.81 1 58 0 1
#> 45.1 17.42 1 54 0 1
#> 160 24.00 0 31 1 0
#> 115 24.00 0 NA 1 0
#> 146 24.00 0 63 1 0
#> 186 24.00 0 45 1 0
#> 34 24.00 0 36 0 0
#> 200 24.00 0 64 0 0
#> 74 24.00 0 43 0 1
#> 165 24.00 0 47 0 0
#> 64 24.00 0 43 0 0
#> 147 24.00 0 76 1 0
#> 64.1 24.00 0 43 0 0
#> 196 24.00 0 19 0 0
#> 22 24.00 0 52 1 0
#> 17 24.00 0 38 0 1
#> 121 24.00 0 57 1 0
#> 172 24.00 0 41 0 0
#> 151 24.00 0 42 0 0
#> 95 24.00 0 68 0 1
#> 1 24.00 0 23 1 0
#> 75 24.00 0 21 1 0
#> 142 24.00 0 53 0 0
#> 11 24.00 0 42 0 1
#> 103 24.00 0 56 1 0
#> 144 24.00 0 28 0 1
#> 48 24.00 0 31 1 0
#> 173 24.00 0 19 0 1
#> 196.1 24.00 0 19 0 0
#> 73 24.00 0 NA 0 1
#> 196.2 24.00 0 19 0 0
#> 165.1 24.00 0 47 0 0
#> 94 24.00 0 51 0 1
#> 95.1 24.00 0 68 0 1
#> 182 24.00 0 35 0 0
#> 185 24.00 0 44 1 0
#> 98 24.00 0 34 1 0
#> 160.1 24.00 0 31 1 0
#> 172.1 24.00 0 41 0 0
#> 185.1 24.00 0 44 1 0
#> 137 24.00 0 45 1 0
#> 2 24.00 0 9 0 0
#> 132 24.00 0 55 0 0
#> 20 24.00 0 46 1 0
#> 95.2 24.00 0 68 0 1
#> 182.1 24.00 0 35 0 0
#> 38 24.00 0 31 1 0
#> 142.1 24.00 0 53 0 0
#> 28 24.00 0 67 1 0
#> 174 24.00 0 49 1 0
#> 1.1 24.00 0 23 1 0
#> 34.1 24.00 0 36 0 0
#> 20.1 24.00 0 46 1 0
#> 185.2 24.00 0 44 1 0
#> 118 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 152 24.00 0 36 0 1
#> 7 24.00 0 37 1 0
#> 74.1 24.00 0 43 0 1
#> 135 24.00 0 58 1 0
#> 54 24.00 0 53 1 0
#> 112 24.00 0 61 0 0
#> 34.2 24.00 0 36 0 0
#> 126 24.00 0 48 0 0
#> 98.1 24.00 0 34 1 0
#> 174.1 24.00 0 49 1 0
#> 21 24.00 0 47 0 0
#> 9 24.00 0 31 1 0
#> 73.1 24.00 0 NA 0 1
#> 44 24.00 0 56 0 0
#> 102 24.00 0 49 0 0
#> 142.2 24.00 0 53 0 0
#> 21.1 24.00 0 47 0 0
#> 74.2 24.00 0 43 0 1
#> 20.2 24.00 0 46 1 0
#> 38.1 24.00 0 31 1 0
#> 112.1 24.00 0 61 0 0
#> 33 24.00 0 53 0 0
#> 19 24.00 0 57 0 1
#> 1.2 24.00 0 23 1 0
#> 173.1 24.00 0 19 0 1
#> 148 24.00 0 61 1 0
#> 146.1 24.00 0 63 1 0
#> 98.2 24.00 0 34 1 0
#> 2.1 24.00 0 9 0 0
#> 176 24.00 0 43 0 1
#> 104 24.00 0 50 1 0
#> 22.1 24.00 0 52 1 0
#> 161 24.00 0 45 0 0
#> 34.3 24.00 0 36 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.576 NA NA NA
#> 2 age, Cure model 0.0144 NA NA NA
#> 3 grade_ii, Cure model -0.182 NA NA NA
#> 4 grade_iii, Cure model 0.830 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00215 NA NA NA
#> 2 grade_ii, Survival model 0.601 NA NA NA
#> 3 grade_iii, Survival model 0.482 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.57611 0.01435 -0.18182 0.82957
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.5
#> Residual Deviance: 251.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.57611028 0.01435053 -0.18181852 0.82957276
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002149028 0.601443083 0.481754732
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.30424011 0.33482262 0.67398049 0.44720573 0.61617543 0.73837261
#> [7] 0.92901419 0.94343446 0.01484339 0.75428110 0.01484339 0.38159735
#> [13] 0.47449622 0.70618678 0.52920169 0.08020896 0.49293758 0.77022946
#> [19] 0.14445536 0.77022946 0.44720573 0.08020896 0.76228371 0.24783922
#> [25] 0.44720573 0.73029286 0.28229508 0.80973371 0.77022946 0.90701440
#> [31] 0.33482262 0.57317936 0.43795580 0.11254405 0.52920169 0.80973371
#> [37] 0.27094518 0.65767097 0.04393208 0.89221199 0.87739205 0.21498370
#> [43] 0.65767097 0.31485569 0.42872270 0.70618678 0.63286831 0.97911864
#> [49] 0.80182123 0.80973371 0.69006558 0.85482604 0.36268640 0.89962702
#> [55] 0.19282790 0.79386104 0.54708785 0.58194027 0.12911616 0.29338935
#> [61] 0.59910378 0.95780386 0.80973371 0.70618678 0.39104112 0.64936236
#> [67] 0.41000065 0.31485569 0.21498370 0.69006558 0.91437494 0.97204477
#> [73] 0.33482262 0.63286831 0.92170905 0.21498370 0.84718871 0.96493487
#> [79] 0.61617543 0.47449622 0.36268640 0.73837261 0.97911864 0.50216102
#> [85] 0.95063491 0.14445536 0.54708785 0.50216102 0.41940779 0.86986809
#> [91] 0.40050731 0.25936446 0.52020582 0.80973371 0.87739205 0.67398049
#> [97] 0.60766852 0.54708785 0.18037106 0.92901419 0.97911864 0.19282790
#> [103] 0.14445536 0.85482604 0.06315770 0.58194027 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 153 190 29 8 130 57 145 187 24 81 24.1 158 88
#> 21.33 20.81 15.45 18.43 16.47 14.46 10.07 9.92 23.89 14.06 23.89 20.14 18.37
#> 180 184 168 108 155 69 155.1 8.1 168.1 60 169 8.2 96
#> 14.82 17.77 23.72 18.29 13.08 23.23 13.08 18.43 23.72 13.15 22.41 18.43 14.54
#> 197 154 155.2 52 190.1 117 179 164 184.1 154.1 136 39 78
#> 21.60 12.63 13.08 10.42 20.81 17.46 18.63 23.60 17.77 12.63 21.83 15.59 23.88
#> 43 49 15 39.1 32 97 180.1 26 127 140 154.2 157 37
#> 12.10 12.19 22.68 15.59 20.90 19.14 14.82 15.77 3.53 12.68 12.63 15.10 12.52
#> 68 159 63 14 110 45 129 139 106 70 154.3 180.2 166
#> 20.62 10.55 22.77 12.89 17.56 17.42 23.41 21.49 16.67 7.38 12.63 14.82 19.98
#> 6 55 32.1 15.1 157.1 93 25 190.2 26.1 61 15.2 177 77
#> 15.64 19.34 20.90 22.68 15.10 10.33 6.32 20.81 15.77 10.12 22.68 12.53 7.27
#> 130.1 88.1 68.1 57.1 127.1 51 183 69.1 110.1 51.1 76 42 105
#> 16.47 18.37 20.62 14.46 3.53 18.23 9.24 23.23 17.56 18.23 19.22 12.43 19.75
#> 66 41 154.4 49.1 29.1 171 110.2 92 145.1 127.2 63.1 69.2 37.1
#> 22.13 18.02 12.63 12.19 15.45 16.57 17.56 22.92 10.07 3.53 22.77 23.23 12.52
#> 86 45.1 160 146 186 34 200 74 165 64 147 64.1 196
#> 23.81 17.42 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 17 121 172 151 95 1 75 142 11 103 144 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173 196.1 196.2 165.1 94 95.1 182 185 98 160.1 172.1 185.1 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 132 20 95.2 182.1 38 142.1 28 174 1.1 34.1 20.1 185.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 82 152 7 74.1 135 54 112 34.2 126 98.1 174.1 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 44 102 142.2 21.1 74.2 20.2 38.1 112.1 33 19 1.2 173.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 146.1 98.2 2.1 176 104 22.1 161 34.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[98]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.0156737 0.8334536 0.6316535
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.2847904743 0.0003433179 0.1961896999
#> grade_iii, Cure model
#> 1.1367402914
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 91 5.33 1 61 0 1
#> 40 18.00 1 28 1 0
#> 69 23.23 1 25 0 1
#> 61 10.12 1 36 0 1
#> 124 9.73 1 NA 1 0
#> 127 3.53 1 62 0 1
#> 187 9.92 1 39 1 0
#> 24 23.89 1 38 0 0
#> 194 22.40 1 38 0 1
#> 40.1 18.00 1 28 1 0
#> 88 18.37 1 47 0 0
#> 101 9.97 1 10 0 1
#> 175 21.91 1 43 0 0
#> 175.1 21.91 1 43 0 0
#> 57 14.46 1 45 0 1
#> 110 17.56 1 65 0 1
#> 69.1 23.23 1 25 0 1
#> 108 18.29 1 39 0 1
#> 99 21.19 1 38 0 1
#> 16 8.71 1 71 0 1
#> 40.2 18.00 1 28 1 0
#> 158 20.14 1 74 1 0
#> 99.1 21.19 1 38 0 1
#> 190 20.81 1 42 1 0
#> 175.2 21.91 1 43 0 0
#> 57.1 14.46 1 45 0 1
#> 58 19.34 1 39 0 0
#> 136 21.83 1 43 0 1
#> 145 10.07 1 65 1 0
#> 8 18.43 1 32 0 0
#> 59 10.16 1 NA 1 0
#> 108.1 18.29 1 39 0 1
#> 154 12.63 1 20 1 0
#> 189 10.51 1 NA 1 0
#> 145.1 10.07 1 65 1 0
#> 43 12.10 1 61 0 1
#> 55 19.34 1 69 0 1
#> 96 14.54 1 33 0 1
#> 111 17.45 1 47 0 1
#> 199 19.81 1 NA 0 1
#> 59.1 10.16 1 NA 1 0
#> 101.1 9.97 1 10 0 1
#> 23 16.92 1 61 0 0
#> 97 19.14 1 65 0 1
#> 168 23.72 1 70 0 0
#> 170 19.54 1 43 0 1
#> 105 19.75 1 60 0 0
#> 125 15.65 1 67 1 0
#> 197 21.60 1 69 1 0
#> 183 9.24 1 67 1 0
#> 14 12.89 1 21 0 0
#> 32 20.90 1 37 1 0
#> 51 18.23 1 83 0 1
#> 153 21.33 1 55 1 0
#> 93 10.33 1 52 0 1
#> 26 15.77 1 49 0 1
#> 136.1 21.83 1 43 0 1
#> 18 15.21 1 49 1 0
#> 76 19.22 1 54 0 1
#> 195 11.76 1 NA 1 0
#> 59.2 10.16 1 NA 1 0
#> 76.1 19.22 1 54 0 1
#> 150 20.33 1 48 0 0
#> 61.1 10.12 1 36 0 1
#> 100 16.07 1 60 0 0
#> 166 19.98 1 48 0 0
#> 106 16.67 1 49 1 0
#> 108.2 18.29 1 39 0 1
#> 43.1 12.10 1 61 0 1
#> 42 12.43 1 49 0 1
#> 29 15.45 1 68 1 0
#> 188 16.16 1 46 0 1
#> 106.1 16.67 1 49 1 0
#> 113 22.86 1 34 0 0
#> 8.1 18.43 1 32 0 0
#> 69.2 23.23 1 25 0 1
#> 24.1 23.89 1 38 0 0
#> 42.1 12.43 1 49 0 1
#> 100.1 16.07 1 60 0 0
#> 25 6.32 1 34 1 0
#> 158.1 20.14 1 74 1 0
#> 145.2 10.07 1 65 1 0
#> 91.1 5.33 1 61 0 1
#> 130 16.47 1 53 0 1
#> 4 17.64 1 NA 0 1
#> 49 12.19 1 48 1 0
#> 42.2 12.43 1 49 0 1
#> 158.2 20.14 1 74 1 0
#> 77 7.27 1 67 0 1
#> 179 18.63 1 42 0 0
#> 6 15.64 1 39 0 0
#> 23.1 16.92 1 61 0 0
#> 194.1 22.40 1 38 0 1
#> 192 16.44 1 31 1 0
#> 184 17.77 1 38 0 0
#> 39 15.59 1 37 0 1
#> 127.1 3.53 1 62 0 1
#> 136.2 21.83 1 43 0 1
#> 66 22.13 1 53 0 0
#> 57.2 14.46 1 45 0 1
#> 36 21.19 1 48 0 1
#> 111.1 17.45 1 47 0 1
#> 113.1 22.86 1 34 0 0
#> 37 12.52 1 57 1 0
#> 124.1 9.73 1 NA 1 0
#> 171 16.57 1 41 0 1
#> 69.3 23.23 1 25 0 1
#> 56 12.21 1 60 0 0
#> 79 16.23 1 54 1 0
#> 166.1 19.98 1 48 0 0
#> 60 13.15 1 38 1 0
#> 194.2 22.40 1 38 0 1
#> 121 24.00 0 57 1 0
#> 172 24.00 0 41 0 0
#> 65 24.00 0 57 1 0
#> 163 24.00 0 66 0 0
#> 120 24.00 0 68 0 1
#> 141 24.00 0 44 1 0
#> 1 24.00 0 23 1 0
#> 156 24.00 0 50 1 0
#> 112 24.00 0 61 0 0
#> 102 24.00 0 49 0 0
#> 115 24.00 0 NA 1 0
#> 72 24.00 0 40 0 1
#> 104 24.00 0 50 1 0
#> 151 24.00 0 42 0 0
#> 148 24.00 0 61 1 0
#> 141.1 24.00 0 44 1 0
#> 44 24.00 0 56 0 0
#> 84 24.00 0 39 0 1
#> 146 24.00 0 63 1 0
#> 146.1 24.00 0 63 1 0
#> 103 24.00 0 56 1 0
#> 27 24.00 0 63 1 0
#> 131 24.00 0 66 0 0
#> 47 24.00 0 38 0 1
#> 33 24.00 0 53 0 0
#> 182 24.00 0 35 0 0
#> 112.1 24.00 0 61 0 0
#> 102.1 24.00 0 49 0 0
#> 31 24.00 0 36 0 1
#> 148.1 24.00 0 61 1 0
#> 115.1 24.00 0 NA 1 0
#> 152 24.00 0 36 0 1
#> 172.1 24.00 0 41 0 0
#> 46 24.00 0 71 0 0
#> 200 24.00 0 64 0 0
#> 84.1 24.00 0 39 0 1
#> 11 24.00 0 42 0 1
#> 73 24.00 0 NA 0 1
#> 132 24.00 0 55 0 0
#> 67 24.00 0 25 0 0
#> 144 24.00 0 28 0 1
#> 135 24.00 0 58 1 0
#> 142 24.00 0 53 0 0
#> 38 24.00 0 31 1 0
#> 162 24.00 0 51 0 0
#> 104.1 24.00 0 50 1 0
#> 38.1 24.00 0 31 1 0
#> 2 24.00 0 9 0 0
#> 33.1 24.00 0 53 0 0
#> 54 24.00 0 53 1 0
#> 142.1 24.00 0 53 0 0
#> 84.2 24.00 0 39 0 1
#> 2.1 24.00 0 9 0 0
#> 62 24.00 0 71 0 0
#> 33.2 24.00 0 53 0 0
#> 142.2 24.00 0 53 0 0
#> 102.2 24.00 0 49 0 0
#> 198 24.00 0 66 0 1
#> 120.1 24.00 0 68 0 1
#> 148.2 24.00 0 61 1 0
#> 82 24.00 0 34 0 0
#> 135.1 24.00 0 58 1 0
#> 176 24.00 0 43 0 1
#> 17 24.00 0 38 0 1
#> 186 24.00 0 45 1 0
#> 74 24.00 0 43 0 1
#> 109 24.00 0 48 0 0
#> 12 24.00 0 63 0 0
#> 112.2 24.00 0 61 0 0
#> 53 24.00 0 32 0 1
#> 38.2 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 115.2 24.00 0 NA 1 0
#> 12.1 24.00 0 63 0 0
#> 75 24.00 0 21 1 0
#> 116 24.00 0 58 0 1
#> 116.1 24.00 0 58 0 1
#> 144.1 24.00 0 28 0 1
#> 19 24.00 0 57 0 1
#> 173 24.00 0 19 0 1
#> 34 24.00 0 36 0 0
#> 7 24.00 0 37 1 0
#> 135.2 24.00 0 58 1 0
#> 27.1 24.00 0 63 1 0
#> 186.1 24.00 0 45 1 0
#> 141.2 24.00 0 44 1 0
#> 33.3 24.00 0 53 0 0
#> 102.3 24.00 0 49 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.285 NA NA NA
#> 2 age, Cure model 0.000343 NA NA NA
#> 3 grade_ii, Cure model 0.196 NA NA NA
#> 4 grade_iii, Cure model 1.14 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0157 NA NA NA
#> 2 grade_ii, Survival model 0.833 NA NA NA
#> 3 grade_iii, Survival model 0.632 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.2847905 0.0003433 0.1961897 1.1367403
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.3
#> Residual Deviance: 245.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.2847904743 0.0003433179 0.1961896999 1.1367402914
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.0156737 0.8334536 0.6316535
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.9898032 0.8061624 0.3458612 0.9565074 0.9949535 0.9763533 0.1713721
#> [8] 0.4761929 0.8061624 0.7805849 0.9707861 0.5397183 0.5397183 0.9085191
#> [15] 0.8249049 0.3458612 0.7859652 0.6386690 0.9818346 0.8061624 0.6901801
#> [22] 0.6386690 0.6738070 0.5397183 0.9085191 0.7355471 0.5822172 0.9623895
#> [29] 0.7697805 0.7859652 0.9252771 0.9623895 0.9474913 0.7355471 0.9050343
#> [36] 0.8294847 0.9707861 0.8383337 0.7588009 0.2973972 0.7292814 0.7228674
#> [43] 0.8869132 0.6177439 0.9791154 0.9219451 0.6652027 0.8012283 0.6285933
#> [50] 0.9535193 0.8831253 0.5822172 0.9015204 0.7474798 0.7474798 0.6820487
#> [57] 0.9565074 0.8754654 0.7099178 0.8470356 0.7859652 0.9474913 0.9318362
#> [64] 0.8979514 0.8715738 0.8470356 0.4332521 0.7697805 0.3458612 0.1713721
#> [71] 0.9318362 0.8754654 0.9871713 0.6901801 0.9623895 0.9898032 0.8595361
#> [78] 0.9443957 0.9318362 0.6901801 0.9845188 0.7643091 0.8906131 0.8383337
#> [85] 0.4761929 0.8636100 0.8202154 0.8943000 0.9949535 0.5822172 0.5239353
#> [92] 0.9085191 0.6386690 0.8294847 0.4332521 0.9285834 0.8553973 0.3458612
#> [99] 0.9412602 0.8676318 0.7099178 0.9186085 0.4761929 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 91 40 69 61 127 187 24 194 40.1 88 101 175 175.1
#> 5.33 18.00 23.23 10.12 3.53 9.92 23.89 22.40 18.00 18.37 9.97 21.91 21.91
#> 57 110 69.1 108 99 16 40.2 158 99.1 190 175.2 57.1 58
#> 14.46 17.56 23.23 18.29 21.19 8.71 18.00 20.14 21.19 20.81 21.91 14.46 19.34
#> 136 145 8 108.1 154 145.1 43 55 96 111 101.1 23 97
#> 21.83 10.07 18.43 18.29 12.63 10.07 12.10 19.34 14.54 17.45 9.97 16.92 19.14
#> 168 170 105 125 197 183 14 32 51 153 93 26 136.1
#> 23.72 19.54 19.75 15.65 21.60 9.24 12.89 20.90 18.23 21.33 10.33 15.77 21.83
#> 18 76 76.1 150 61.1 100 166 106 108.2 43.1 42 29 188
#> 15.21 19.22 19.22 20.33 10.12 16.07 19.98 16.67 18.29 12.10 12.43 15.45 16.16
#> 106.1 113 8.1 69.2 24.1 42.1 100.1 25 158.1 145.2 91.1 130 49
#> 16.67 22.86 18.43 23.23 23.89 12.43 16.07 6.32 20.14 10.07 5.33 16.47 12.19
#> 42.2 158.2 77 179 6 23.1 194.1 192 184 39 127.1 136.2 66
#> 12.43 20.14 7.27 18.63 15.64 16.92 22.40 16.44 17.77 15.59 3.53 21.83 22.13
#> 57.2 36 111.1 113.1 37 171 69.3 56 79 166.1 60 194.2 121
#> 14.46 21.19 17.45 22.86 12.52 16.57 23.23 12.21 16.23 19.98 13.15 22.40 24.00
#> 172 65 163 120 141 1 156 112 102 72 104 151 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141.1 44 84 146 146.1 103 27 131 47 33 182 112.1 102.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 148.1 152 172.1 46 200 84.1 11 132 67 144 135 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 162 104.1 38.1 2 33.1 54 142.1 84.2 2.1 62 33.2 142.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102.2 198 120.1 148.2 82 135.1 176 17 186 74 109 12 112.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 38.2 185 12.1 75 116 116.1 144.1 19 173 34 7 135.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27.1 186.1 141.2 33.3 102.3
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[99]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001094481 0.033081233 0.280281422
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.329842712 0.004534657 -0.021118982
#> grade_iii, Cure model
#> 0.893637939
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 155 13.08 1 26 0 0
#> 43 12.10 1 61 0 1
#> 14 12.89 1 21 0 0
#> 60 13.15 1 38 1 0
#> 66 22.13 1 53 0 0
#> 106 16.67 1 49 1 0
#> 175 21.91 1 43 0 0
#> 194 22.40 1 38 0 1
#> 42 12.43 1 49 0 1
#> 77 7.27 1 67 0 1
#> 177 12.53 1 75 0 0
#> 88 18.37 1 47 0 0
#> 158 20.14 1 74 1 0
#> 159 10.55 1 50 0 1
#> 52 10.42 1 52 0 1
#> 39 15.59 1 37 0 1
#> 110 17.56 1 65 0 1
#> 124 9.73 1 NA 1 0
#> 89 11.44 1 NA 0 0
#> 145 10.07 1 65 1 0
#> 81 14.06 1 34 0 0
#> 188 16.16 1 46 0 1
#> 36 21.19 1 48 0 1
#> 180 14.82 1 37 0 0
#> 155.1 13.08 1 26 0 0
#> 43.1 12.10 1 61 0 1
#> 180.1 14.82 1 37 0 0
#> 155.2 13.08 1 26 0 0
#> 77.1 7.27 1 67 0 1
#> 158.1 20.14 1 74 1 0
#> 111 17.45 1 47 0 1
#> 123 13.00 1 44 1 0
#> 97 19.14 1 65 0 1
#> 88.1 18.37 1 47 0 0
#> 49 12.19 1 48 1 0
#> 149 8.37 1 33 1 0
#> 114 13.68 1 NA 0 0
#> 130 16.47 1 53 0 1
#> 60.1 13.15 1 38 1 0
#> 110.1 17.56 1 65 0 1
#> 154 12.63 1 20 1 0
#> 170 19.54 1 43 0 1
#> 16 8.71 1 71 0 1
#> 50 10.02 1 NA 1 0
#> 15 22.68 1 48 0 0
#> 25 6.32 1 34 1 0
#> 43.2 12.10 1 61 0 1
#> 169 22.41 1 46 0 0
#> 90 20.94 1 50 0 1
#> 180.2 14.82 1 37 0 0
#> 70 7.38 1 30 1 0
#> 66.1 22.13 1 53 0 0
#> 129 23.41 1 53 1 0
#> 30 17.43 1 78 0 0
#> 18 15.21 1 49 1 0
#> 101 9.97 1 10 0 1
#> 108 18.29 1 39 0 1
#> 51 18.23 1 83 0 1
#> 69 23.23 1 25 0 1
#> 45 17.42 1 54 0 1
#> 81.1 14.06 1 34 0 0
#> 157 15.10 1 47 0 0
#> 153 21.33 1 55 1 0
#> 39.1 15.59 1 37 0 1
#> 124.1 9.73 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 49.1 12.19 1 48 1 0
#> 58 19.34 1 39 0 0
#> 45.1 17.42 1 54 0 1
#> 99 21.19 1 38 0 1
#> 134 17.81 1 47 1 0
#> 197 21.60 1 69 1 0
#> 117 17.46 1 26 0 1
#> 16.1 8.71 1 71 0 1
#> 113 22.86 1 34 0 0
#> 189 10.51 1 NA 1 0
#> 130.1 16.47 1 53 0 1
#> 97.1 19.14 1 65 0 1
#> 97.2 19.14 1 65 0 1
#> 177.1 12.53 1 75 0 0
#> 188.1 16.16 1 46 0 1
#> 154.1 12.63 1 20 1 0
#> 26 15.77 1 49 0 1
#> 60.2 13.15 1 38 1 0
#> 195 11.76 1 NA 1 0
#> 183 9.24 1 67 1 0
#> 77.2 7.27 1 67 0 1
#> 155.3 13.08 1 26 0 0
#> 114.1 13.68 1 NA 0 0
#> 107 11.18 1 54 1 0
#> 61 10.12 1 36 0 1
#> 105 19.75 1 60 0 0
#> 170.1 19.54 1 43 0 1
#> 195.1 11.76 1 NA 1 0
#> 93 10.33 1 52 0 1
#> 85 16.44 1 36 0 0
#> 184 17.77 1 38 0 0
#> 159.1 10.55 1 50 0 1
#> 129.1 23.41 1 53 1 0
#> 8 18.43 1 32 0 0
#> 197.1 21.60 1 69 1 0
#> 134.1 17.81 1 47 1 0
#> 127 3.53 1 62 0 1
#> 92 22.92 1 47 0 1
#> 41 18.02 1 40 1 0
#> 140 12.68 1 59 1 0
#> 171 16.57 1 41 0 1
#> 133 14.65 1 57 0 0
#> 30.1 17.43 1 78 0 0
#> 166 19.98 1 48 0 0
#> 150 20.33 1 48 0 0
#> 63 22.77 1 31 1 0
#> 7 24.00 0 37 1 0
#> 143 24.00 0 51 0 0
#> 116 24.00 0 58 0 1
#> 3 24.00 0 31 1 0
#> 173 24.00 0 19 0 1
#> 27 24.00 0 63 1 0
#> 182 24.00 0 35 0 0
#> 54 24.00 0 53 1 0
#> 126 24.00 0 48 0 0
#> 19 24.00 0 57 0 1
#> 65 24.00 0 57 1 0
#> 121 24.00 0 57 1 0
#> 148 24.00 0 61 1 0
#> 120 24.00 0 68 0 1
#> 28 24.00 0 67 1 0
#> 46 24.00 0 71 0 0
#> 120.1 24.00 0 68 0 1
#> 103 24.00 0 56 1 0
#> 53 24.00 0 32 0 1
#> 48 24.00 0 31 1 0
#> 3.1 24.00 0 31 1 0
#> 62 24.00 0 71 0 0
#> 118 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 137 24.00 0 45 1 0
#> 82 24.00 0 34 0 0
#> 118.1 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 138 24.00 0 44 1 0
#> 1 24.00 0 23 1 0
#> 163 24.00 0 66 0 0
#> 65.1 24.00 0 57 1 0
#> 137.1 24.00 0 45 1 0
#> 198 24.00 0 66 0 1
#> 67 24.00 0 25 0 0
#> 138.1 24.00 0 44 1 0
#> 1.1 24.00 0 23 1 0
#> 83 24.00 0 6 0 0
#> 28.1 24.00 0 67 1 0
#> 98 24.00 0 34 1 0
#> 12 24.00 0 63 0 0
#> 33 24.00 0 53 0 0
#> 109 24.00 0 48 0 0
#> 64 24.00 0 43 0 0
#> 122 24.00 0 66 0 0
#> 48.1 24.00 0 31 1 0
#> 84 24.00 0 39 0 1
#> 95.1 24.00 0 68 0 1
#> 163.1 24.00 0 66 0 0
#> 33.1 24.00 0 53 0 0
#> 82.1 24.00 0 34 0 0
#> 161 24.00 0 45 0 0
#> 161.1 24.00 0 45 0 0
#> 47 24.00 0 38 0 1
#> 62.1 24.00 0 71 0 0
#> 11 24.00 0 42 0 1
#> 17 24.00 0 38 0 1
#> 27.1 24.00 0 63 1 0
#> 62.2 24.00 0 71 0 0
#> 132 24.00 0 55 0 0
#> 67.1 24.00 0 25 0 0
#> 161.2 24.00 0 45 0 0
#> 72 24.00 0 40 0 1
#> 19.1 24.00 0 57 0 1
#> 115 24.00 0 NA 1 0
#> 121.1 24.00 0 57 1 0
#> 27.2 24.00 0 63 1 0
#> 178 24.00 0 52 1 0
#> 142 24.00 0 53 0 0
#> 38 24.00 0 31 1 0
#> 173.1 24.00 0 19 0 1
#> 147 24.00 0 76 1 0
#> 17.1 24.00 0 38 0 1
#> 2 24.00 0 9 0 0
#> 138.2 24.00 0 44 1 0
#> 196 24.00 0 19 0 0
#> 21 24.00 0 47 0 0
#> 44 24.00 0 56 0 0
#> 80.1 24.00 0 41 0 0
#> 28.2 24.00 0 67 1 0
#> 151 24.00 0 42 0 0
#> 3.2 24.00 0 31 1 0
#> 173.2 24.00 0 19 0 1
#> 112 24.00 0 61 0 0
#> 143.1 24.00 0 51 0 0
#> 84.1 24.00 0 39 0 1
#> 72.1 24.00 0 40 0 1
#> 34 24.00 0 36 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.330 NA NA NA
#> 2 age, Cure model 0.00453 NA NA NA
#> 3 grade_ii, Cure model -0.0211 NA NA NA
#> 4 grade_iii, Cure model 0.894 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00109 NA NA NA
#> 2 grade_ii, Survival model 0.0331 NA NA NA
#> 3 grade_iii, Survival model 0.280 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.329843 0.004535 -0.021119 0.893638
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 253.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.329842712 0.004534657 -0.021118982 0.893637939
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001094481 0.033081233 0.280281422
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.70050805 0.81999040 0.74306173 0.67486823 0.13631061 0.51664854
#> [7] 0.15964630 0.12396892 0.79447459 0.95201506 0.77740153 0.36389856
#> [13] 0.25044235 0.85340175 0.87000821 0.58836772 0.44208962 0.89485015
#> [19] 0.65761385 0.56187717 0.20647155 0.62316685 0.70050805 0.81999040
#> [25] 0.62316685 0.70050805 0.95201506 0.25044235 0.47044278 0.73443703
#> [31] 0.32455225 0.36389856 0.80302088 0.93573883 0.53498977 0.67486823
#> [37] 0.44208962 0.76029635 0.29340641 0.91951858 0.09824385 0.97595614
#> [43] 0.81999040 0.11114394 0.22840968 0.62316685 0.94387934 0.13631061
#> [49] 0.01784411 0.47983802 0.60571892 0.90309263 0.38364718 0.39355347
#> [55] 0.04446090 0.49838055 0.65761385 0.61444615 0.19469776 0.58836772
#> [61] 0.98399784 0.80302088 0.31406337 0.49838055 0.20647155 0.41312555
#> [67] 0.17173108 0.46097316 0.91951858 0.07213055 0.53498977 0.32455225
#> [73] 0.32455225 0.77740153 0.56187717 0.76029635 0.57952789 0.67486823
#> [79] 0.91130976 0.95201506 0.70050805 0.84499230 0.88659933 0.28258948
#> [85] 0.29340641 0.87831948 0.55286965 0.43236812 0.85340175 0.01784411
#> [91] 0.35385749 0.17173108 0.41312555 0.99201235 0.05892263 0.40334899
#> [97] 0.75168411 0.52584988 0.64892062 0.47983802 0.27174444 0.23943964
#> [103] 0.08525438 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 155 43 14 60 66 106 175 194 42 77 177 88 158
#> 13.08 12.10 12.89 13.15 22.13 16.67 21.91 22.40 12.43 7.27 12.53 18.37 20.14
#> 159 52 39 110 145 81 188 36 180 155.1 43.1 180.1 155.2
#> 10.55 10.42 15.59 17.56 10.07 14.06 16.16 21.19 14.82 13.08 12.10 14.82 13.08
#> 77.1 158.1 111 123 97 88.1 49 149 130 60.1 110.1 154 170
#> 7.27 20.14 17.45 13.00 19.14 18.37 12.19 8.37 16.47 13.15 17.56 12.63 19.54
#> 16 15 25 43.2 169 90 180.2 70 66.1 129 30 18 101
#> 8.71 22.68 6.32 12.10 22.41 20.94 14.82 7.38 22.13 23.41 17.43 15.21 9.97
#> 108 51 69 45 81.1 157 153 39.1 91 49.1 58 45.1 99
#> 18.29 18.23 23.23 17.42 14.06 15.10 21.33 15.59 5.33 12.19 19.34 17.42 21.19
#> 134 197 117 16.1 113 130.1 97.1 97.2 177.1 188.1 154.1 26 60.2
#> 17.81 21.60 17.46 8.71 22.86 16.47 19.14 19.14 12.53 16.16 12.63 15.77 13.15
#> 183 77.2 155.3 107 61 105 170.1 93 85 184 159.1 129.1 8
#> 9.24 7.27 13.08 11.18 10.12 19.75 19.54 10.33 16.44 17.77 10.55 23.41 18.43
#> 197.1 134.1 127 92 41 140 171 133 30.1 166 150 63 7
#> 21.60 17.81 3.53 22.92 18.02 12.68 16.57 14.65 17.43 19.98 20.33 22.77 24.00
#> 143 116 3 173 27 182 54 126 19 65 121 148 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 46 120.1 103 53 48 3.1 62 118 95 137 82 118.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 138 1 163 65.1 137.1 198 67 138.1 1.1 83 28.1 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 33 109 64 122 48.1 84 95.1 163.1 33.1 82.1 161 161.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47 62.1 11 17 27.1 62.2 132 67.1 161.2 72 19.1 121.1 27.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 142 38 173.1 147 17.1 2 138.2 196 21 44 80.1 28.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151 3.2 173.2 112 143.1 84.1 72.1 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[100]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.0003242654 -0.1256708412 -0.1162769832
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.88603102 0.01374345 0.35543050
#> grade_iii, Cure model
#> 0.80467022
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564add25e1d8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 157 15.10 1 47 0 0
#> 50 10.02 1 NA 1 0
#> 106 16.67 1 49 1 0
#> 129 23.41 1 53 1 0
#> 68 20.62 1 44 0 0
#> 10 10.53 1 34 0 0
#> 139 21.49 1 63 1 0
#> 123 13.00 1 44 1 0
#> 81 14.06 1 34 0 0
#> 68.1 20.62 1 44 0 0
#> 110 17.56 1 65 0 1
#> 199 19.81 1 NA 0 1
#> 153 21.33 1 55 1 0
#> 40 18.00 1 28 1 0
#> 194 22.40 1 38 0 1
#> 134 17.81 1 47 1 0
#> 127 3.53 1 62 0 1
#> 129.1 23.41 1 53 1 0
#> 188 16.16 1 46 0 1
#> 92 22.92 1 47 0 1
#> 171 16.57 1 41 0 1
#> 63 22.77 1 31 1 0
#> 125 15.65 1 67 1 0
#> 167 15.55 1 56 1 0
#> 134.1 17.81 1 47 1 0
#> 25 6.32 1 34 1 0
#> 140 12.68 1 59 1 0
#> 52 10.42 1 52 0 1
#> 49 12.19 1 48 1 0
#> 60 13.15 1 38 1 0
#> 39 15.59 1 37 0 1
#> 133 14.65 1 57 0 0
#> 60.1 13.15 1 38 1 0
#> 188.1 16.16 1 46 0 1
#> 169 22.41 1 46 0 0
#> 180 14.82 1 37 0 0
#> 158 20.14 1 74 1 0
#> 93 10.33 1 52 0 1
#> 155 13.08 1 26 0 0
#> 25.1 6.32 1 34 1 0
#> 113 22.86 1 34 0 0
#> 99 21.19 1 38 0 1
#> 170 19.54 1 43 0 1
#> 117 17.46 1 26 0 1
#> 69 23.23 1 25 0 1
#> 36 21.19 1 48 0 1
#> 154 12.63 1 20 1 0
#> 59 10.16 1 NA 1 0
#> 171.1 16.57 1 41 0 1
#> 197 21.60 1 69 1 0
#> 76 19.22 1 54 0 1
#> 5 16.43 1 51 0 1
#> 127.1 3.53 1 62 0 1
#> 139.1 21.49 1 63 1 0
#> 61 10.12 1 36 0 1
#> 59.1 10.16 1 NA 1 0
#> 45 17.42 1 54 0 1
#> 85 16.44 1 36 0 0
#> 197.1 21.60 1 69 1 0
#> 110.1 17.56 1 65 0 1
#> 114 13.68 1 NA 0 0
#> 181 16.46 1 45 0 1
#> 45.1 17.42 1 54 0 1
#> 86 23.81 1 58 0 1
#> 183 9.24 1 67 1 0
#> 30 17.43 1 78 0 0
#> 195 11.76 1 NA 1 0
#> 39.1 15.59 1 37 0 1
#> 190 20.81 1 42 1 0
#> 97 19.14 1 65 0 1
#> 145 10.07 1 65 1 0
#> 25.2 6.32 1 34 1 0
#> 127.2 3.53 1 62 0 1
#> 6 15.64 1 39 0 0
#> 6.1 15.64 1 39 0 0
#> 169.1 22.41 1 46 0 0
#> 111 17.45 1 47 0 1
#> 189 10.51 1 NA 1 0
#> 59.2 10.16 1 NA 1 0
#> 41 18.02 1 40 1 0
#> 127.3 3.53 1 62 0 1
#> 52.1 10.42 1 52 0 1
#> 57 14.46 1 45 0 1
#> 55 19.34 1 69 0 1
#> 108 18.29 1 39 0 1
#> 63.1 22.77 1 31 1 0
#> 50.1 10.02 1 NA 1 0
#> 10.1 10.53 1 34 0 0
#> 70 7.38 1 30 1 0
#> 70.1 7.38 1 30 1 0
#> 181.1 16.46 1 45 0 1
#> 166 19.98 1 48 0 0
#> 108.1 18.29 1 39 0 1
#> 108.2 18.29 1 39 0 1
#> 171.2 16.57 1 41 0 1
#> 187 9.92 1 39 1 0
#> 29 15.45 1 68 1 0
#> 100 16.07 1 60 0 0
#> 167.1 15.55 1 56 1 0
#> 124 9.73 1 NA 1 0
#> 127.4 3.53 1 62 0 1
#> 181.2 16.46 1 45 0 1
#> 56 12.21 1 60 0 0
#> 177 12.53 1 75 0 0
#> 5.1 16.43 1 51 0 1
#> 10.2 10.53 1 34 0 0
#> 13 14.34 1 54 0 1
#> 183.1 9.24 1 67 1 0
#> 184 17.77 1 38 0 0
#> 29.1 15.45 1 68 1 0
#> 79 16.23 1 54 1 0
#> 55.1 19.34 1 69 0 1
#> 173 24.00 0 19 0 1
#> 82 24.00 0 34 0 0
#> 73 24.00 0 NA 0 1
#> 144 24.00 0 28 0 1
#> 147 24.00 0 76 1 0
#> 64 24.00 0 43 0 0
#> 21 24.00 0 47 0 0
#> 74 24.00 0 43 0 1
#> 116 24.00 0 58 0 1
#> 198 24.00 0 66 0 1
#> 64.1 24.00 0 43 0 0
#> 2 24.00 0 9 0 0
#> 161 24.00 0 45 0 0
#> 95 24.00 0 68 0 1
#> 62 24.00 0 71 0 0
#> 198.1 24.00 0 66 0 1
#> 11 24.00 0 42 0 1
#> 148 24.00 0 61 1 0
#> 87 24.00 0 27 0 0
#> 165 24.00 0 47 0 0
#> 109 24.00 0 48 0 0
#> 122 24.00 0 66 0 0
#> 121 24.00 0 57 1 0
#> 22 24.00 0 52 1 0
#> 152 24.00 0 36 0 1
#> 115 24.00 0 NA 1 0
#> 65 24.00 0 57 1 0
#> 11.1 24.00 0 42 0 1
#> 165.1 24.00 0 47 0 0
#> 83 24.00 0 6 0 0
#> 75 24.00 0 21 1 0
#> 144.1 24.00 0 28 0 1
#> 7 24.00 0 37 1 0
#> 27 24.00 0 63 1 0
#> 75.1 24.00 0 21 1 0
#> 198.2 24.00 0 66 0 1
#> 33 24.00 0 53 0 0
#> 65.1 24.00 0 57 1 0
#> 144.2 24.00 0 28 0 1
#> 95.1 24.00 0 68 0 1
#> 174 24.00 0 49 1 0
#> 21.1 24.00 0 47 0 0
#> 48 24.00 0 31 1 0
#> 12 24.00 0 63 0 0
#> 119 24.00 0 17 0 0
#> 102 24.00 0 49 0 0
#> 71 24.00 0 51 0 0
#> 38 24.00 0 31 1 0
#> 135 24.00 0 58 1 0
#> 102.1 24.00 0 49 0 0
#> 141 24.00 0 44 1 0
#> 19 24.00 0 57 0 1
#> 141.1 24.00 0 44 1 0
#> 200 24.00 0 64 0 0
#> 172 24.00 0 41 0 0
#> 141.2 24.00 0 44 1 0
#> 1 24.00 0 23 1 0
#> 3 24.00 0 31 1 0
#> 196 24.00 0 19 0 0
#> 7.1 24.00 0 37 1 0
#> 178 24.00 0 52 1 0
#> 178.1 24.00 0 52 1 0
#> 103 24.00 0 56 1 0
#> 162 24.00 0 51 0 0
#> 67 24.00 0 25 0 0
#> 186 24.00 0 45 1 0
#> 94 24.00 0 51 0 1
#> 3.1 24.00 0 31 1 0
#> 160 24.00 0 31 1 0
#> 146 24.00 0 63 1 0
#> 116.1 24.00 0 58 0 1
#> 75.2 24.00 0 21 1 0
#> 17 24.00 0 38 0 1
#> 31 24.00 0 36 0 1
#> 19.1 24.00 0 57 0 1
#> 87.1 24.00 0 27 0 0
#> 54 24.00 0 53 1 0
#> 48.1 24.00 0 31 1 0
#> 186.1 24.00 0 45 1 0
#> 48.2 24.00 0 31 1 0
#> 11.2 24.00 0 42 0 1
#> 103.1 24.00 0 56 1 0
#> 46 24.00 0 71 0 0
#> 116.2 24.00 0 58 0 1
#> 95.2 24.00 0 68 0 1
#> 144.3 24.00 0 28 0 1
#> 131 24.00 0 66 0 0
#> 182 24.00 0 35 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.886 NA NA NA
#> 2 age, Cure model 0.0137 NA NA NA
#> 3 grade_ii, Cure model 0.355 NA NA NA
#> 4 grade_iii, Cure model 0.805 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000324 NA NA NA
#> 2 grade_ii, Survival model -0.126 NA NA NA
#> 3 grade_iii, Survival model -0.116 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.88603 0.01374 0.35543 0.80467
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.3
#> Residual Deviance: 252.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.88603102 0.01374345 0.35543050 0.80467022
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.0003242654 -0.1256708412 -0.1162769832
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.628609035 0.398433002 0.012994588 0.168951839 0.782872448 0.114293964
#> [7] 0.720864450 0.679855162 0.168951839 0.329837313 0.132076055 0.291042045
#> [13] 0.087772705 0.300774187 0.948399244 0.012994588 0.507337078 0.035971034
#> [19] 0.408378548 0.053847230 0.537564336 0.588025506 0.300774187 0.917250584
#> [25] 0.731176319 0.813503441 0.772521483 0.690122143 0.567838041 0.649094050
#> [31] 0.690122143 0.507337078 0.070830421 0.638852532 0.187242648 0.834103721
#> [37] 0.710568110 0.917250584 0.044915979 0.141354779 0.206087882 0.349220299
#> [43] 0.027244679 0.141354779 0.741502908 0.408378548 0.096788836 0.234200783
#> [49] 0.477262839 0.948399244 0.114293964 0.844480458 0.378840395 0.467212933
#> [55] 0.096788836 0.329837313 0.437699826 0.378840395 0.004315249 0.875687208
#> [61] 0.368962840 0.567838041 0.159530491 0.243756645 0.854869877 0.917250584
#> [67] 0.948399244 0.547721465 0.547721465 0.070830421 0.359078523 0.281345613
#> [73] 0.948399244 0.813503441 0.659332558 0.215549132 0.253346691 0.053847230
#> [79] 0.782872448 0.896442516 0.896442516 0.437699826 0.196668762 0.253346691
#> [85] 0.253346691 0.408378548 0.865271851 0.608283927 0.527426125 0.588025506
#> [91] 0.948399244 0.437699826 0.762184959 0.751845683 0.477262839 0.782872448
#> [97] 0.669586464 0.875687208 0.320052267 0.608283927 0.497230121 0.215549132
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000
#>
#> $Time
#> 157 106 129 68 10 139 123 81 68.1 110 153 40 194
#> 15.10 16.67 23.41 20.62 10.53 21.49 13.00 14.06 20.62 17.56 21.33 18.00 22.40
#> 134 127 129.1 188 92 171 63 125 167 134.1 25 140 52
#> 17.81 3.53 23.41 16.16 22.92 16.57 22.77 15.65 15.55 17.81 6.32 12.68 10.42
#> 49 60 39 133 60.1 188.1 169 180 158 93 155 25.1 113
#> 12.19 13.15 15.59 14.65 13.15 16.16 22.41 14.82 20.14 10.33 13.08 6.32 22.86
#> 99 170 117 69 36 154 171.1 197 76 5 127.1 139.1 61
#> 21.19 19.54 17.46 23.23 21.19 12.63 16.57 21.60 19.22 16.43 3.53 21.49 10.12
#> 45 85 197.1 110.1 181 45.1 86 183 30 39.1 190 97 145
#> 17.42 16.44 21.60 17.56 16.46 17.42 23.81 9.24 17.43 15.59 20.81 19.14 10.07
#> 25.2 127.2 6 6.1 169.1 111 41 127.3 52.1 57 55 108 63.1
#> 6.32 3.53 15.64 15.64 22.41 17.45 18.02 3.53 10.42 14.46 19.34 18.29 22.77
#> 10.1 70 70.1 181.1 166 108.1 108.2 171.2 187 29 100 167.1 127.4
#> 10.53 7.38 7.38 16.46 19.98 18.29 18.29 16.57 9.92 15.45 16.07 15.55 3.53
#> 181.2 56 177 5.1 10.2 13 183.1 184 29.1 79 55.1 173 82
#> 16.46 12.21 12.53 16.43 10.53 14.34 9.24 17.77 15.45 16.23 19.34 24.00 24.00
#> 144 147 64 21 74 116 198 64.1 2 161 95 62 198.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11 148 87 165 109 122 121 22 152 65 11.1 165.1 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 144.1 7 27 75.1 198.2 33 65.1 144.2 95.1 174 21.1 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 119 102 71 38 135 102.1 141 19 141.1 200 172 141.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 3 196 7.1 178 178.1 103 162 67 186 94 3.1 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 116.1 75.2 17 31 19.1 87.1 54 48.1 186.1 48.2 11.2 103.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46 116.2 95.2 144.3 131 182
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> Formula blueprint:
#>
#> # Predictors: 2
#> # Outcomes: 2
#> Intercept: TRUE
#> Novel Levels: FALSE
#> Composition: tibble
#> Indicators: traditional
#>
#> $cure_blueprint
#> Formula blueprint:
#>
#> # Predictors: 2
#> # Outcomes: 0
#> Intercept: TRUE
#> Novel Levels: FALSE
#> Composition: tibble
#> Indicators: traditional
#>